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Greenhouse 


A Life-Cycle Assessment 
of Emissions and Sinks 







SOLID WASTE MANAGEMENT AND GREENHOUSE GASES 
A Life-Cycle Assessment of Emissions and Sinks 


3 rd EDITION 


NOV 0 6.200 b 




September 2006 




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TABLE OF CONTENTS 


Executive Summary: Background and Findings.ES-1 

ES. 1 GHGs and Climate Change.ES-1 

ES.2 Climate Change Initiatives in the United States.ES-2 

ES.3 Municipal Solid Waste and GHG Emissions.ES-4 

ESA Genesis and Applications of the Report.ES-5 

ES.5 The Impact of Municipal Solid Waste on GHG Emissions.ES-6 

ES.6 Results of the Analysis.ES-12 

ES.7 Other Life-Cycle GHG Analyses and Tools.ES-17 

ES.8 Limitations of the Analysis.ES-19 

1. Life-Cycle Methodology.1 

1.1 The Overall Framework: a Streamlined Life-Cycle Inventory.2 

1.2 MSW Materials Considered in the Streamlined Life-Cycle Inventory.2 

1.3 Key Inputs for the Streamlined Life-Cycle Inventory.5 

1.4 Summary of the Life-Cycle Stages.8 

1.5 Estimating and Comparing Net GHG Emissions.14 

2. Raw Materials Acquisition and Manufacturing.17 

2.1 GHG Emissions from Energy Use in Raw Materials Acquisition and 

Manufacturing.17 

2.2 Nonenergy GHG Emissions from Manufacturing and Raw Materials Acquisition.21 

2.3 Results.21 

2.4 Limitations.21 

3. Source Reduction and Recycling.31 

3.1 GHG Implications of Source Reduction.31 

3.2 GHG Implications of Recycling.32 

3.3 Open Loop Recycling.36 

3.4 Source Reduction Through Material Substitution.38 

3.5 Forest Carbon Sequestration.38 

3.6 Limitations.45 

4. Composting.49 

4.1 Potential GHG Emissions.49 

4.2 Potential Carbon Storage.50 

4.3 Net GHG Emissions From Composting.60 

4.4 Limitations.61 

5. Combustion.65 

5.1 Methodology.67 

5.2 Results.76 

5.3 Limitations.76 

6. Landfilling.79 

6.1 CH 4 Generation and Carbon Storage for Organic Materials.80 

6.2 Fates of Landfill CH 4 .86 









































6.3 Utility C0 2 Emissions Avoided.88 

6.4 Net GHG Emissions from Landfilling.88 

6.5 Limitations.90 

7. Energy Impacts.97 

7.1 Methodolgy for Developing Energy Factors.97 

7.2 Energy Implications for Waste Management Options.98 

7.3 Applying Energy Factors.99 

7.4 Relating Energy Savings to GHG Benefits.100 

8. Energy and Emission Benefits.107 

8.1 Net GHG Emissions for Each Waste Management Option.107 

8.2 Applying GHG Emission Factors.109 

8.3 Tools and Other Life-Cycle GHG Analyses.112 

8.4 Opportunities for GHG Reductions.114 

Appendix A. Raw Materials Extraction Reference Point.125 

Appendix B. Carbon Dioxide Equivalent Emission Factors.127 

Appendix C. Roadmap from the Second Edition.135 


















TABLE OF EXHIBITS 


Exhibit ES-1 Net GHG Emissions from Source Reduction and MSW Management Options.ES-8 

Exhibit ES-2 Components of Net Emissions for Various MSW Management Strategies.ES-10 

Exhibit ES-3 Greenhouse Gas Sources and Sinks Associated with the Material Life Cycle.ES-11 

Exhibit ES-4 Net GHG Emissions from Source Reduction and MSW Management Options.ES-14 

Exhibit ES-5 GHG Emissions of MSW Management Options Compared to Landfilling.ES-15 

Exhibit 1-1 Materials Analyzed and Energy-related Data Sources.4 

Exhibit 1-2 Greenhouse Gas Sources and Sinks Associated with the Material Life Cycle.9 

Exhibit 1-3 Components of Net Emissions for Various MSW Management Strategies.10 

Exhibit 2-1 Carbon Coefficients For Selected Fuels (Per Million Btu).23 

Exhibit 2-2 GHG Emissions from the Manufacture of Selected Materials.24 

Exhibit 2-3 Process GHG Emissions Per Ton of Product Manufactured from Virgin Inputs.26 

Exhibit 2-4 Transportation GHG Emissions Per Ton of Product Manufactured from Virgin Inputs.27 

Exhibit 2-5 Process GHG Emissions Per Ton of Product Manufactured from Recycled Inputs.28 

Exhibit 2-6 Transportation GHG Emissions Per Ton of Product Manufactured from Recycled 

Inputs.29 

Exhibit 2-7 Retail Transport Energy and Emissions.30 

Exhibit 3-1 GHG Emissions for Source Reduction.34 

Exhibit 3-2 Composition of Mixed Paper Categories.35 

Exhibit 3-3 Loss Rates For Recovered Materials.36 

Exhibit 3-4 Relationship Between Paper Recovery and Pulpwood Harvest.40 

Exhibit 3-5 Increased Forest Carbon Storage per Unit of Reduced Pulpwood Harvest.41 

Exhibit 3-6 Change, with respect to baseline, in carbon stocks for FORCARB II pools.42 

Exhibit 3-7 Forest Carbon Storage from Recycling and Source Reduction.43 

Exhibit 3-8 GHG Emissions for Recycling.46 

Exhibit 4-1 Soil Carbon Storage—Colorado and Iowa sites; 10, 20, and 40 tons-per-acre 

Application Rates.56 

Exhibit 4-2 Incremental Carbon Storage as a Function of Nitrogen Application Rate.57 

Exhibit 4-3 Total Soil C; Iowa Site, Com Harvested for Grain.58 

Exhibit 4-4 Incremental Carbon Storage: MTCE/Wet Ton Versus Time.59 

Exhibit 4-5 Difference in Carbon Storage Between Compost Addition and Base Case.60 

Exhibit 4-6 Net GHG Emissions from Composting.61 

Exhibit 5-1 Gross Emissions of GHGs from MSW Combustion.70 

Exhibit 5-2 Avoided Utility GHG Emissions from Combustion at Mass Bum and RDF Facilities.71 

Exhibit 5-3 Estimating the Weighted Average Carbon Coefficient of the U.S. Average Mix of 

Fuels Used to Generate Electricity.73 

Exhibit 5-4 Estimating the Emission Factor for Utility Generated Electricity.74 

Exhibit 5-5 Avoided GHG Emissions Due to Increased Steel Recovery from MSW at WTE 

Facilities.75 

Exhibit 5-6 Net GHG Emissions from Combustion at WTE Facilities.77 

Exhibit 6-1 Landfill Carbon Mass Balance.81 

Exhibit 6-2 Experimental and Adjusted Values for CH 4 Yield and Carbon Storage.84 

Exhibit 6-3 CH 4 Yield for Solid Waste Components.85 

Exhibit 6-4 Carbon Storage for Solid Waste Components.85 









































Exhibit 6-5 Composition of Mixed Paper Categories from Barlaz Experiments.87 

Exhibit 6-6 GHG Emissions from CH 4 Generation.89 

Exhibit 6-7 Calculation to Estimate Utility GHGs Avoided through Combustion of Landfill CH 4 .92 

Exhibit 6-8 Net GHG Emissions from Landfilling.93 

Exhibit 6-9 Net GHG Emissions from CH 4 Generation at Landfills with Recovery.94 

Exhibit 6-10 Net GHG Emissions from CH 4 Generation at Landfills with Recovery.95 

Exhibit 7-1 Energy Savings per Ton Recycled.98 

Exhibit 7-2 Recycling GHG Benefits Attributable to Energy Savings (Recycling vs. Landfilling).99 

Exhibit 7-3 Energy Consumed/Avoided for Source Reduction.101 

Exhibit 7-4 Energy Consumed/A voided for Recycling.102 

Exhibit 7-5 Energy Consumed/Avoided for Combustion.103 

Exhibit 7-6 Energy Consumed/Avoided for Landfilling.104 

Exhibit 7-7 Net Energy Consumed/Avoided from Source Reduction and MSW Management 

Options.105 

Exhibit 7-8 Energy Consumed/Avoided for MSW Management Options Compared to Landfilling.106 

Exhibit 8-1 Recommended Surrogates for Voluntary Reporting.108 

Exhibit 8-2 GHG Emissions for Source Reduction.116 

Exhibit 8-3 GHG Emissions for Recycling.117 

Exhibit 8-4 GHG Emissions for Composting.118 

Exhibit 8-5 GHG Emissions for Combustion.119 

Exhibit 8-6 GHG Emissions for Landfilling.120 

Exhibit 8-7 Net GHG Emissions from Source Reduction and MSW Management Options.121 

Exhibit 8-8 Net GHG Emissions of MSW Management Options Compared to Landfilling.122 

Exhibit A-l Net GHG Emissions from Source Reduction and MSW Management Options - 

Emissions Counted from a Raw Materials Extraction Reference Point.125 

Exhibit A-2 Net GHG Emissions from Source Reduction and MSW Management Options - Emissions 

Counted from a Raw Materials Extraction Reference Point.126 

Exhibit B-l Net GHG Emissions from Source Reduction and MSW Management Options - 

Emissions Counted from a Waste Generation Reference Point (MTC0 2 E/Ton).127 

Exhibit B-2 GHG Emissions of MSW Management Options Compared to Landfilling 

(MTC0 2 E/Ton).128 

Exhibit B-3 GHG Emissions for Source Reduction (MTC02E/Ton of Material Source Reduced).129 

Exhibit B-4 Recycling (GHG Emissions in MTC02E/Ton).130 

Exhibit B-5 Composting (GHG Emissions in MTC02E/Ton).131 

Exhibit B-6 Combustion (GHG Emissions in MTC02E/Ton).132 

Exhibit B-7 Landfilling (GHG Emissions in MTC02E/Ton).133 

Exhibit C-l GHG Emissions for Source Reduction.137 

Exhibit C-2 GHG Emissions for Recycling.138 

Exhibit C-3 Net GHG Emissions from Composting.139 

Exhibit C-4 Gross Emissions of GHGs from MSW Combustion.139 

Exhibit C-5 Net GHG Emissions from Landfilling.140 






































EXECUTIVE SUMMARY: BACKGROUND AND FINDINGS 


In the 21 st century, management of municipal solid waste (MSW) continues to be an important 
environmental challenge facing the United States. In 2003, the United States generated 236.2 million 
tons 1 of MSW, an increase of 15 percent over 1990 generation levels and 168 percent over 1980 levels. 2 
Climate change is also a serious issue, and the United States is embarking on a number of voluntary 
actions to reduce the emissions of greenhouse gases (GHGs) that can intensify climate change. By 
presenting material-specific GHG emission factors for various waste management options, this report 
examines the interrelationship between MSW management and climate change. 

Among the efforts to slow the potential for climate change are measures to reduce emissions of 
carbon dioxide (C0 2 ) from energy use, decrease emissions of methane (CH 4 ) and other non-carbon- 
dioxide GHGs, and promote long-term storage of carbon in forests and soil. Management options for 
MSW provide many opportunities to affect these processes, directly or indirectly. This report integrates 
information on the GHG implications of various management options for some of the most common 
materials in MSW. To EPA’s knowledge, this work represents the most complete national study on GHG 
emissions and sinks from solid waste management practices. The report’s findings may be used to 
support a variety of programs and activities, including voluntary reporting of emission reductions from 
waste management practices. 

ES.l GHGs AND CLIMATE CHANGE 

Climate change is a serious international environmental concern and the subject of much 
research. Many, if not most, of the readers of this report will have a general understanding of the 
greenhouse effect and climate change. However, for those who are not familiar with the topic, a brief 
explanation follows. 3 

A naturally occurring shield of “greenhouse gases’’ (primarily water vapor, C0 2 , CH 4 , and nitrous 
oxide), comprising 1 to 2 percent of the Earth’s atmosphere, absorbs some of the solar radiation that 
would otherwise be radiated into space and helps warm the planet to a comfortable, livable temperature 
range. Without this natural “greenhouse effect,” the average temperature on Earth would be 
approximately -2 degrees Fahrenheit, rather than the current 57 degrees Fahrenheit. 4 

Many scientists are concerned about the significant increase in the concentration of C0 2 and other 
GHGs in the atmosphere. Since the preindustrial era, atmospheric concentrations of C0 2 have increased 
by nearly 30 percent and CH 4 concentrations have more than doubled. There is a growing international 
scientific consensus that this increase has been caused, at least in part, by human activity, primarily the 


1 All references to tonnage of waste in this report are in short tons. All references to tons of carbon or C0 2 
equivalent are in metric tons (i.e., MTCE per short ton of material). 

2 EPA Office of Solid Waste, Municipal Solid Waste in the United States: 2003 Facts and Figures, EPA (2005), p. 2. 

3 For more detailed infonnation on climate change, please see the 2005 Inventory ofU.S. Greenhouse Gas Emissions 
and Sinks: 1990-2003, available online at: 

http://vosemite.epa.gov/oar/globalwanning.nsf/content/ResourceCenterPublicationsGHGEmissions.html 

(September 2005); and Climate Change 2001: The Scientific Basis (J.T. Houghton, et al., eds. Intergovernmental 

Panel on Climate Change [IPCC]; published by Cambridge University Press, 2001). To obtain a list of additional 
documents addressing climate change, access EPA’s global warming Web site at 

http://vosemite.epa.gov/oar/globalwarming.nsf/content/index.html . 

4 Climate Change 2001: The Scientific Basis, op. cit., pp. 89-90. 


ES-1 









burning of fossil fuels (coal, oil, and natural gas) for such activities as generating electricity and driving 
cars. 5 

Moreover, in international scientific circles a consensus is growing that the buildup of C0 2 and 
other GHGs in the atmosphere will lead to major environmental changes such as (1) rising sea levels that 
may flood coastal and river delta communities; (2) shrinking mountain glaciers and reduced snow cover 
that may diminish fresh water resources; (3) the spread of infectious diseases and increased heat-related 
mortality; (4) possible loss in biological diversity and other impacts on ecosystems; and (5) agricultural 
shifts such as impacts on crop yields and productivity. 6 Although reliably detecting the trends in climate 
due to natural variability is difficult, the most accepted current projections suggest that the rate of climate 
change attributable to GHGs will far exceed any natural climate changes that have occurred during the 
last 1,000 years. 7 * 

Many of these changes appear to be occurring already. Global mean surface temperatures already 
have increased by about 1 degree Fahrenheit over the past century. A reduction in the northern 
hemisphere’s snow cover, a decrease in Arctic sea ice, a rise in sea level, and an increase in the frequency 
of extreme rainfall events all have been documented. 5 

Such important environmental changes pose potentially significant risks to humans, social 
systems, and the natural world. Many uncertainties remain regarding the precise timing, magnitude, and 
regional patterns of climate change and the extent to which mankind and nature can adapt to any changes. 
It is clear, however, that changes will not be easily reversed for many decades or even centuries because 
of the long atmospheric lifetimes of GHGs and the inertia of the climate system. 

ES.2 CLIMATE CHANGE INITIATIVES IN THE UNITED STATES 

In 1992, world leaders and citizens from some 200 countries met in Rio de Janeiro, Brazil, to 
confront global ecological concerns. At this “Earth Summit,” 154 nations, including the United States, 
signed the United Nations Framework Convention on Climate Change (UNFCCC), an international 
agreement to address the danger of global climate change. The objective of the Convention was to 
stabilize GHG concentrations in the atmosphere over time at a level at which manmade climate 
disruptions would be minimized. 

By signing the Convention, countries made a voluntary commitment to reduce GHGs or take 
other actions to stabilize emissions of GHGs. All Parties to the Convention were required to develop and 
periodically update national inventories of their GHG emissions. The United States ratified the 
Convention in October 1992. One year later, the United States issued its Climate Change Action Plan 
(CCAP), which calls for cost-effective domestic actions and voluntary cooperation with states, local 
governments, industry, and citizens to reduce GHG emissions. 

In order to achieve the goals outlined in the Climate Change Action Plan , EPA initiated several 
voluntary programs to realize the most cost-effective opportunities for reducing emissions. For example, 
in 1994 EPA created the Landfill Methane Outreach Program, which aims to reduce landfill CH 4 
emissions by facilitating the development of projects that use landfill gas to produce energy. 9 In the same 
year, EPA introduced the Climate and Waste Program to capture the climate benefits of a broader set of 
waste-related initiatives (e.g., recycling, source reduction). In 2001 EPA started the Green Power 
Partnership. This partnership aids organizations that want to obtain some or all of their power from 


5 Ibid., p. 7. 

6 J.J. McCarthy, et al., eds. 2001. Climate Change 2001: Impacts, Adaptation, and Vulnerability. IPCC. Cambridge 
University Press, pp. 9-13. 

7 Climate Change 2001: The Scientific Basis, op. cit., p. 2. 

5 Ibid., p. 4. 

9 Available at the U.S. Environmental Protection Agency’s Landfill Methane Outreach Program website: 
http://www.epa.gov/lmop . Toll-free hotline number: 800-782-7937. 


ES-2 




renewable energy sources, including landfill gas. The program has more than 500 partners, whose green 
power purchasing commitments now exceed two million megawatt-hours. 

To date, EPA’s voluntary partnership programs for climate protection have achieved substantial 
environmental results. In 2004 alone, these programs reduced GHG emissions by 57 million metric tons 
of carbon equivalent (MMTCE)—the equivalent of eliminating the annual emissions from approximately 
45 million cars. 10 In addition, substantial CH 4 emission reductions—estimated at more than one MMTCE 
for the period from 1999-2000—are being obtained as an ancillary benefit of Clean Air Act (CAA) 
regulatory requirements that were promulgated in 1996, limiting emissions from landfills. 

Many corporations that are concerned about climate change and wish to take action have joined 
EPA’s Climate Leaders program. Participating corporations set reduction targets for themselves and 
agree to report their emissions annually and monitor progress toward their target. Participants come from 
a broad range of sectors, including energy and oil, pharmaceuticals, banking, high-tech, and 
manufacturing. * 11 As of April 2006, there were 86 Climate Leaders, 46 of whom had set reduction targets. 
Together, these 79 companies account for about 8 percent of U.S. GHG emissions; the targets, if met, will 
prevent emissions of more than eight MMTCE per year. 12 

The U.S. Department of Energy (DOE) administers a voluntary GHG reporting program under 
section 1605(b) of the Energy Policy Act of 1992. This program enables companies and other entities to 
report their GHG emissions and to gain recognition for reductions they have implemented, including 
reductions through MSW management innovations. The 1605(b) program is currently finalizing revised 
guidelines and provisions. 13 

There has been significant action on the regional level as well. The six New England states 
(Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont) joined with the 
eastern Canadian provinces in 2001 to write the New England Govemors/Eastem Canadian Premiers 
(NEG/ECP) Climate Change Action Plan. The Governors and Premiers agreed to commit their states and 
provinces to write and implement action plans that will achieve the goals of reducing emissions to 1990 
levels by 2010, and to 10 percent below 1990 emissions by 2020. 14 Some of these states were among the 
first to write climate change action plans, as a result of commitment to the NEG/ECP goals. Seven 
northeastern states (plus four observer states) have joined together to form the Regional Greenhouse Gas 
Initiative (RGGI), which, when it comes into effect, will be a cap-and-trade system for power plant GHG 
emissions, the first of its kind in the US. The West Coast Governors’ Global Warming Initiative was 
started by the Governors of California, Oregon, and Washington in 2003. The goals of the initiative 
include combining purchasing power to improve the efficiency of vehicle fleets and improving appliance 
efficiency standards. They are considering the creation of a regional cap-and-trade system. California is 
also contemplating a cap-and-trade system that would include not just power plants, but also other 
stationary sources of GHG emissions, such as semiconductor manufacturers. 

Meanwhile, an increasing number of states have instituted their own voluntary actions to reduce 
emissions. Forty-two states and Puerto Rico have inventoried their GHG emissions. Twenty-eight states 


10 EPA Press Release, “10 Billion Saved on Energy Bills,” 4 October 2005; car equivalent calculation available 
online at the U.S. Climate Technology Cooperation Gateway’s Greenhouse Gas Equivalencies Calculator: 
http://www.usctcgatewav.net/tool/ . 

11 Available at the EPA’s Climate Leaders website: http://www.epa.gov/climateleaders 

12 John Millet, “Five Climate Leaders Companies Reach Their Greenhouse Gas Reduction Goals,” U.S. 
Environmental Protection Agency press release. 18 January 2006. 

I3 DOE, “Enhancing DOE’s Voluntary Reporting of Greenhouse Gases (1605(b)) Program.” Department of Energy. 
Available online at: http://www.pi.energv.gov/enhancingGHGregistry 

14 The New England Govemors/Eastem Canadian Premiers website: http://www.negc.org/premiers.html 


ES-3 







and Puerto Rico have completed or initiated state action plans, which outline steps to reduce emissions. 
Twenty-five of these action plans have incorporated the reduction of waste into their GHG mitigation 
strategies. Finally, at least 11 states—including California, Illinois, New Hampshire, and Wisconsin—are 
in the process of establishing GHG registries, which enable companies and other entities to report 
voluntary emission reductions. 16 

Many states are engaging in further study of climate change implications and, in some cases, 
enacting legislation. For example, 22 states and the District of Columbia have renewable portfolio 
standards (RPS), requiring that electricity producers obtain a certain amount of their power from 
renewable sources. In most of these states, waste-to-energy facilities and landfill gas are permitted 
energy sources. 

Oregon recently created its Strategy for Greenhouse Gas Reductions, outlining recommended 
actions to reduce GHG emissions at the state level. Ten of these actions fall under the category 
“Materials Use, Recovery, and Waste Disposal” and include such strategies as increasing “Bottle Bill” 
refunds to 10 cents from 5 and widening the scope to include all beverage containers except milk. 

Cities and towns also are taking action. More than 160 municipalities in the United States have 
joined the Cities for Climate Protection (CCP) campaign run by ICLEI (Local Governments for 
Sustainability). CCP members agree to inventory their GHG emissions, set a reduction target, write an 
action plan to reduce emissions, and implement the plan. One of the key sectors that the CCP program 
focuses on is waste, and many cities have taken action on this issue. For example, Seattle has increased 
its recycling rate, reduced landfill CH 4 emissions, and banned recyclables from garbage. 

ES.3 MUNICIPAL SOLID WASTE AND GHG EMISSIONS 

What does MSW have to do with rising sea levels, higher temperatures, and GHG emissions? 

For many wastes, the materials in MSW represent what is left over after a long series of steps: (1) 
extraction and processing of raw materials; (2) manufacture of products; (3) transportation of materials 
and products to markets; (4) use by consumers; and (5) waste management. 

Virtually every step along this “life cycle” impacts GHG emissions. Solid waste management 
decisions can reduce GHGs by affecting one or more of the following: 

(1) Energy consumption (specifically, combustion of fossil fuels) associated with making, 
transporting, using, and disposing the product or material that becomes a waste. 

(2) Nonenergy-related manufacturing emissions , such as the C0 2 released when limestone is 
converted to lime (e.g., steel manufacturing). 

(3) CH 4 emissions from landfills where the waste is disposed. 

(4) CCE and nitrous oxide (NiO) emissions from waste combustion. 

(5) Carbon sequestration , which refers to natural or manmade processes that remove carbon from 
the atmosphere and store it for long periods or permanently. 

The first four mechanisms add GHGs to the atmosphere and contribute to global wanning. The 
fifth—carbon sequestration —reduces GHG concentrations by removing C0 2 from the atmosphere. 


15 EPA’s Global Wanning—Actions, “State” webpage. Available at: 
http://vosemite.epa.gov/oar/globalwanning.nsf/content/ActionsState.html . 

16 Progressive Policy Institute, State Greenhouse Gas Registries, 5 September 2003. Available at: 
http://www.ppionline.org/ppi ci.cfm?knlgAreaID=l 16&subsecID=900039&contentID=251287 


ES-4 











Forest growth is one mechanism for sequestering carbon; if more biomass is grown than is removed 
(through harvest or decay), the amount of carbon stored in trees increases, and thus carbon is sequestered. 

Different wastes and waste management options have different implications for energy 
consumption, CH 4 emissions, and carbon sequestration. Source reduction and recycling of paper 
products, for example, reduce energy consumption, decrease combustion and landfill emissions, and 
increase forest carbon sequestration. 

ES.4 GENESIS AND APPLICATIONS OF THE REPORT 

Recognizing the potential for source reduction and recycling of municipal solid waste to reduce 
GHG emissions, EPA included a source reduction and recycling initiative in the original 1994 Climate 
Change Action Plan and set an emission reduction goal based on a preliminary analysis of the potential 
benefits of these activities. It was clear that a rigorous analysis would be needed to gauge more 
accurately the total GHG emission reductions achievable through source reduction and recycling. 

That all of the options for managing MSW should be considered also became clear. By 
addressing a broader set of MSW management options, a more comprehensive picture of the GHG 
benefits of voluntary actions in the waste sector could be determined, and the relative GHG impacts of 
various waste management approaches could be assessed. To this end, EPA launched a major research 
effort, the results of which were published in the first edition of this report in September 1998. A second 
edition of the report was published in May 2002. This third edition of the report includes additional 
materials and incorporates updated data affecting some of the material-specific results. The emission 
factors 1 presented will continue to be updated and improved as more data become available. The latest 
emission factors, reflecting these ongoing revisions, can be found on EPA’s “Measuring Greenhouse Gas 
Emissions from Waste” website. 18 

The primary application of the GHG emission factors in this report is to support waste-related 
decisionmaking in the context of climate change. By quantifying the climate impacts of waste 
management decisions, the factors in this report enable municipalities, companies, and other waste 
management decisionmakers to measure the benefits of their actions. In recent years, the emission factors 
have been applied for this purpose in a number of ways. In conjunction with the DOE, EPA has used 
these estimates to develop guidance for voluntary reporting of GHG reductions, as authorized by 
Congress in Section 1605(b) of the Energy Policy Act of 1992. However, under the new, more rigorous 
1605(b) reporting guidelines, emissions reductions from solid waste management practices would be 
reported separately under “other indirect emissions” and not included in the main corporate inventory. 

Other applications have included quantifying the GHG reductions from voluntary programs 
aimed at source reduction and recycling, such as EPA's WasteWise, Pay-As-You-Throw, and Coal 
Combustion Products Partnership (C 2 P 2 ) programs. EPA also has worked with the Climate Neutral 
Network to develop company-specific GHG “footprints” for the network’s member companies, who have 
pledged to become GHG “neutral” through emission reductions or offset activities. 

Currently, Climate Leaders does not record GHG emissions reductions from the purchase of 
recycled-content paper or the recycling of waste paper in a Partners' inventory. Climate Leaders focuses 
on corporate-level GHG inventory emissions calculations and reporting. Calculating GHG emission 
reductions from recycling uses a project-level approach which can involve a high level of uncertainty 
from the calculation of avoided emissions. The approach used to calculate a corporate GHG emissions 
inventory uses activity data, such as fuel consumption, which allow for a higher level of accuracy than the 


17 An amount of waste (in short tons) is multiplied by an emission factor (in MTCE/ton) to yield GHG emissions in 
MTCE. Each emission factor is specific to a particular waste management practice and to a particular material type. 

18 EPA’s Global Warming—Waste, “Measuring Greenhouse Gas Emissions from Waste” webpage. Available at: 
http://www.epa.gov/mswclimate 


ES-5 



avoided emissions approach. Therefore, Climate Leaders does not currently count these GHG emissions 
reductions from avoided emissions. However, as the methodology for calculating project level reductions 
from the use of recycled paper and the recycling of waste paper evolves, EPA will reconsider recognizing 
Partners for these activities. Since the reductions from improved materials management activities do lead 
to global reductions in GHG emissions - EPA encourages Partners to continue efforts in promoting these 
programs and measuring their impact. 

The international community has shown considerable interest in using the emission factors—or 
adapted versions—to develop GHG emission estimates for non-U.S. solid waste streams. 10 For example, 
Environment Canada and Natural Resources Canada recently employed EPA’s life-cycle methodology 
and components of its analysis to develop a set of Canada-specific GHG emission factors to support 
analysis of waste-related mitigation opportunities. 20 

Additionally, EPA worked with ICLEI to incorporate GHG emission factors into its municipal 
GHG accounting software. Currently, more than 600 communities worldwide participate in ICLEI’s 
Cities for Climate Protection Campaign, which helps them establish a GHG emission reduction target and 
implement a comprehensive local action plan designed to achieve that target. Currently, EPA is exploring 
other options for broadening the use of its research internationally. 

To make it easier for organizations to use these emission factors, EPA created the Waste 
Reduction Model (WARM), the Recycled Content (ReCon) Tool, and the Durable Goods Calculator 
(DGC). All of these tools are discussed in more detail in Section ES.7, below. 

ES.5 THE IMPACT OF MUNICIPAL SOLID WASTE MANAGEMENT ON GHG 
EMISSIONS 

To measure the GHG impacts of MSW, EPA first decided which wastes to analyze. The universe 
of materials and products found in MSW was surveyed and those that are most likely to have the greatest 
impact on GHGs were identified. These determinations were based on (1) the quantity generated; (2) the 
differences in energy use for manufacturing a product from virgin versus recycled inputs; and (3) the 
potential contribution of materials to CH 4 generation in landfills. By this process, EPA limited the 
analysis to the following 21 single-material items: 21 

• Three categories of metal: 

• Aluminum Cans; 

• Steel Cans; 

• Copper Wire; 

• Glass; 

• Three types of plastic: 

• HDPE (high-density polyethylene); 

• LDPE (low-density polyethylene); 

• PET (polyethylene terephthalate); 


19 Note that waste composition and product life cycles vary significantly among countries. This report may assist 
other countries by providing a methodological framework and benchmark data for developing GHG emission 
estimates for their solid waste streams. 

20 Environment Canada. 2001. Determination of the Impact of Waste Management Activities on Greenhouse Gas 
Emissions. Prepared by ICF Consulting, Torrie-Smith Associates, and Enviros-RIS. 

21 The following materials are new to this edition: copper wire, clay bricks, concrete, fly ash, tires, carpet, and 
personal computers. 


ES-6 



• Six categories of paper products: 

• Corrugated Cardboard; 

• Magazines/Third-class Mail; 

• Newspaper; 

• Office Paper; 

• Phonebooks; 

• Textbooks; 

• Two types of wood products: 

• Dimensional Lumber; 

• Medium-density Fiberboard; 

• Food Discards; 

• Yard Trimmings; 

• Clay Bricks; 

• Concrete; 

• Fly Ash; and 

• Tires. 

EPA’s researchers also included two products that are composites of several materials: 

• Carpet; and 

• Personal Computers. 

The foregoing materials constitute more than 65 percent, by weight, of MSW, as shown in 
Exhibit ES-1 (this figure excludes clay bricks, concrete, copper wire, fly ash, and medium-density 
fiberboard, which were not included in the waste characterization report cited here). 22 

In addition to the materials listed above, EPA examined the GHG implications of managing 
mixed plastics, mixed metals, mixed organics, mixed recyclables, mixed MSW, and three definitions of 
mixed paper. Each of these mixed categories is summarized below. 

• Mixed plastics are composed of HDPE, LDPE, and PET and are estimated by taking a weighted 
average of the 2003 recovery rates for these three plastic types. 

• Mixed metals are composed of steel cans and aluminum cans and are estimated by taking a 
weighted average of the 2003 recovery rates for these two metal types. 

• Mixed organics are a weighted average of food discards and yard trimmings, using generation 
rates for 2003. 

• Mixed recyclables are materials that are typically recycled. As used in this report, the tenn 
includes the items listed in Exhibit ES-1, except food discards and yard trimmings. The emission 
factors reported for mixed recyclables represent the average GHG emissions for these materials, 
weighted by the tonnages at which they were recycled in 2003. 


22 Note that these data are based on national averages. The composition of solid waste varies locally and regionally; 
local or state-level data should be used when available. 


ES-7 




• Mixed MSW comprises the waste material 
typically discarded by households and 
collected by curbside collection vehicles; it 
does not include white goods (e.g., 
refrigerators, toasters) or industrial waste. 
This report analyzes mixed MSW on an “as- 
disposed” (rather than “as-generated”) basis. 

• Mixed paper is recycled in large quantities 
and is an important class of scrap material in 
many recycling programs. Presenting a 
single definition of mixed paper is difficult, 
however, because recovered paper varies 
considerably, depending on the source. For 
purposes of this report, EPA identified three 
categories of mixed paper according to the 
dominant source—broad (includes most 
categories of recyclable paper products), 
office, and residential (see Exhibit 3-2 for 
definitions of mixed paper categories). 

The EPA researchers developed a 
streamlined life-cycle inventory for each of the 
selected materials. The analysis is streamlined in the 
sense that it examines GHG emissions only and is not 
a comprehensive environmental analysis of all 
emissions from municipal solid waste management 
options. 23 

EPA focused on those aspects of the life 
cycle that have the potential to emit GHGs as 
materials change from their raw states to products 
and then to waste. Exhibit ES-3 shows the steps in 
the life cycle at which GHGs are emitted, carbon 
sequestration is affected, and utility energy is 
displaced. As shown, EPA examined the potential 
for these effects at the following points in a product’s 
life cycle: 

• Raw material acquisition (fossil fuel energy 
and other emissions, and changes in forest 
carbon sequestration); 


Exhibit ES-1 

U.S. Generation of MSW For Materials in This 
_ Report _ 


Material 

MSW Generation by 
Weight (percent) 

Aluminum Cans 

0.6% 

Steel Cans 

1.1% 

Copper Wire 

N/A 

Glass 

4.5% 

HDPE 

1.6% 

LDPE 

1.3% 

PET 

0.9% 

Corrugated Cardboard 

12.6% 

Magazines/Third-class 

Mail 

3.2% 

Newspaper 

5.4% 

Office Paper 

3.0% 

Phonebooks 

0.3% 

Textbooks 

0.4% 

Dimensional Lumber 3 

3.5% 

Medium-density 

Fiberboard 

N/A 

Food Discards 

11.0% 

Yard Trimmings 

12.1% 

Carpet 

1.2% 

Personal Computers 

N/A 

Clay Bricks 

N/A 

Concrete 

N/A 

Fly Ash 

N/A 

Tires 

2.0% 

TOTAL 

64.8% 


a Listed in Municipal Solid Waste in the United States: 2003 
Facts and Figures as "Wood—Containers and Packaging. 
Source: EPA. 2005. Municipal Solid Waste in the United 
States: 2003 Facts and Figures, EPA 530-F-05-003. 


23 EPA’s Office of Research and Development (ORD) performed a more extensive application of life-cycle 
assessment for various waste management options for MSW. A decision support tool (DST) and life-cycle 
inventory (LCI) database for North America have been developed with funding by ORD through a cooperative 
agreement with the Research Triangle Institute (RTI) (CR823052). This methodology is based on a multimedia, 
multipollutant approach and includes analysis of GHG emissions as well as a broader set of emissions (air, water, 
and waste) associated with MSW operations. The LCI database is expected to be released in the summer of 2006. 
The website address for further information is: http://www.rti.org/ . then search the term “DST.” 


ES-8 































• Manufacturing (fossil fuel 
energy emissions); and 

• Waste management (CO 2 
emissions associated with 
composting, nonbiogenic C0 2 
and N 2 0 emissions from 
combustion, and CH 4 emissions 
from landfills); these emissions 
are offset to some degree by 
carbon storage in soil and 
landfills, as well as avoided 
utility emissions from energy 
recovery at combustors and 
landfills. 

At each point in the material life 
cycle, EPA also considered 
transportation-related energy emissions. 

Estimates of GHG emissions associated 
with electricity used in the raw materials 
acquisition and manufacturing steps are 
based on the nation’s current mix of 
energy sources, 24 including fossil fuels, 
hydropower, and nuclear power. 

However, when estimating GHG 
emission reductions attributable to utility 
emissions avoided, the electricity use 
displaced by waste management practices 
is assumed to be 100 percent fossil- 
derived. 2 '' 

EPA did not analyze the GHG 
emissions typically associated with 
consumer use of products because the 
primary concern of this report was 

end-of-life management. Although the consumer-use stage of life can in some cases (e.g., personal 
computers) account for significant energy consumption, the energy consumed during use would be 
approximately the same whether the product was made from virgin or recycled inputs. 

To apply the GHG estimates developed in this report, one must compare a baseline scenario with 
an alternative scenario, on a life-cycle basis. For example, one could compare a baseline scenario, where 
10 tons of office paper are manufactured, used, and landfilled, to an alternative scenario, where 10 tons 
are manufactured, used, and recycled. 

Exhibit ES-2 shows how GHG sources and sinks are affected by each waste management 
strategy. For example, the top row of the exhibit shows that source reduction 26 (1) reduces GHG 


Improvements to the New Edition 

This report is the third edition of Greenhouse Gas 

Emissions from Management of Selected Materials in Municipal 

Solid Waste. This edition includes the following improvements: 

• Develops emission factors for seven new material types: 
copper wire, clay bricks, concrete, fly ash, tires, carpet, and 
personal computers; 

• Incorporates new energy data into calculations of utility 
offsets; 

• Updates U.S. landfill gas collection characteristics to reflect 
the latest values from the U.S. Greenhouse Gas Inventory; 

• Revises carbon coefficients and fuel use for national average 
electricity generation; 

• Includes a discussion of emerging issues in the area of 
climate change and waste management; 

• Includes a chapter on the energy reduction benefits of solid 
waste management. 

• Provides an updated list of suggested proxy values for 
voluntary reporting of GHG emission reductions; 

• Includes a discussion of open-loop recycling, as it relates to 
EPA’s factors for fly ash, carpet, personal computers, and 
mixed paper; 

• Adds retail transport to the methodology; 

• Updates the current mix of recycled/virgin inputs for various 
materials; and 

• Includes an updated analysis of forest carbon sequestration 
and moves the discussion into the recycling chapter. 

These changes and/or revisions are described in more detail 

throughout the report and in Appendix C. 


24 The emissions are based on the current national grid mix, as opposed to regional grids. 

25 EPA adopted this approach based on suggestions from several reviewers who argued that fossil fuels should be 
regarded as the marginal fuel displaced by waste-to-energy and landfill gas recovery systems. 

26 The source reduction techniques the EPA researchers analyzed involve using less of a given product—e.g., by 
making aluminum cans with less aluminum (“lightweighting”); double-sided rather than single-sided photocopying; 


ES-9 






emissions from raw materials acquisition and manufacturing; (2) results in an increase in forest carbon 
sequestration; and (3) does not result in GHG emissions from waste management. The sum of emissions 
(and sinks) across all steps in the life cycle represents net emissions. 


Exhibit ES-2 Components of Net Emissions for Various MSW Management Strategies 


MSW 

Management 

Strategy 

GHG Sources and Sinks 

Raw Materials Acquisition and 
Manufacturing 

Changes in Forest or 
Soil Carbon Storage 

Waste Management 

Source Reduction 

Decrease in GHG emissions, 
relative to the baseline of 
manufacturing 

Increase in forest carbon 
sequestration (for 
organic materials) 

No emissions/sinks 

Recycling 

Decrease in GHG emissions due 
to lower energy requirements 
(compared to manufacture from 
virgin inputs) and avoided 
process nonenergy GHGs 

Increase in forest carbon 
sequestration (for 
organic materials) 

Process and transportation 
emissions associated with recycling 
are counted in the manufacturing 
stage 

Composting (food 
discards, yard 
trimmings) 

NA 

Increase in soil carbon 
storage 

Compost machinery emissions and 
transportation emissions 

Combustion 

NA 

NA 

Nonbiogenic CO 2 , N 2 0 emissions, 
avoided utility emissions, and 
transportation emissions 

Landfilling 

NA 

NA 

CH 4 emissions, long-term carbon 
storage, avoided utility emissions, 
and transportation emissions 


NA = Not Applicable 


or reuse of a product. EPA did not analyze source reduction through material substitution (except in the special case 
of fly ash)—e.g., substituting plastic boxes for corrugated paper boxes. Nor did EPA estimate the potential for 
source reduction of chemical fertilizers and pesticides with increased production and use of compost. For a 
discussion of source reduction with material substitution, see Section 3.3. 


ES-10 































ES.6 


RESULTS OF THE ANALYSIS 


Management of municipal solid waste presents many opportunities for GHG emission 
reductions. Source reduction and recycling can reduce GHG emissions at the manufacturing 
stage, increase forest carbon sequestration, and avoid landfill CH 4 emissions. When waste is 
combusted, energy recovery displaces electricity generated by utilities by burning fossil fuels 
(thus reducing GHG emissions from the utility sector), and landfill CH 4 emissions are avoided. 
Landfill CH 4 emissions can be reduced by using gas recovery systems and by diverting organic 
materials from landfills. Landfill CH 4 can be flared or utilized for its energy potential. When 
used for its energy potential, landfill CH 4 displaces fossil fuels, as with MSW combustion. 

In order to support a broad portfolio of climate change mitigation activities covering a 
range of GHGs, various methodologies for estimating emissions are needed. The primary result 
of this research is the development of material-specific GHG emission factors that can be used to 
account for the climate change benefits of waste management practices. 

Exhibit ES-4 presents the GHG impacts of source reduction, recycling, composting, 
combustion, and landfilling. The impacts are calculated per short ton of waste managed. Please 
note that the emission factors presented in this report are intended to be compared with one 
another. They are not meant to reflect absolute values, but instead reflect the impact of choosing 
one waste management option over another for a given material type. This convention enabled 
EPA to calculate emission impacts from a waste generation reference point (i.e., from the 
moment a material is discarded). This process is in contrast to a typical life-cycle analysis, which 
reflects a raw materials extraction reference point. “Upstream” emissions and sinks are captured 
in EPA’s streamlined methodology once a baseline waste management practice is compared to an 
alternative waste management practice. 

In addition, this report does not include emissions from the use phase of a product’s life, 
since use does not have an effect on the waste management emissions of a product. EPA took 
this approach because expert review of the first edition indicated that a waste management 
perspective would be more useful and comprehensible to waste managers, at whom this report is 
chiefly aimed . 27 The results are the same in the end, because it is the difference between the 
baseline and the alternative waste disposal scenarios that show the GHG savings from different 
treatment options; therefore, all tables and analyses in this report use a “waste generation” 
reference point. Exhibit ES-4 presents these values in MTCE/short ton of waste . 28 In these 
tables, emissions for 1 ton of a given material are presented across different management options. 
The life-cycle GHG emissions for each of the first four waste management strategies—source 
reduction, recycling, composting, and combustion—are compared to the GHG emissions from 
landfilling in Exhibit ES-5. These exhibits show the GHG values for each of the first four 
management strategies, minus the GHG values for landfilling. With these exhibits, one may 
compare the GHG emissions of changing management of 1 ton of each material from landfilling 
(often viewed as the baseline waste management strategy) to one of the other waste management 
options. 

All values shown in Exhibit ES-4 and Exhibit ES-5 are for national average conditions 
(e.g., average fuel mix for raw material acquisition and manufacturing using recycled inputs; 
typical efficiency of a mass bum combustion unit; and national average landfill gas collection 
rates). GHG emissions are sensitive to some factors that vary on a local basis, and thus site- 
specific emissions will differ from those summarized here. 


27 For the same results using a raw material extraction reference point, please see Appendix A. 
2S For the same results in MTCCLE, please see Appendix B. 


ES-12 



Following is a discussion of the principal GHG emissions and sinks for each waste 
management practice and the effect that they have on the emission factors: 

• Source reduction, in general, represents an opportunity to reduce GHG emissions in a 
significant way. For many materials, the reduction in energy-related C0 2 emissions from 
the raw material acquisition and manufacturing process, and the absence of emissions 
from waste management, combine to reduce GHG emissions more than other options do. 

• For most materials, recycling represents the second best opportunity to reduce GHG 
emissions. For these materials, recycling reduces energy-related C0 2 emissions in the 
manufacturing process (although not as dramatically as source reduction) and avoids 
emissions from waste management. Paper recycling increases the sequestration of forest 
carbon. 

• Composting is a management option for food discards and yard trimmings. The net GHG 
emissions from composting are lower than landfilling for food discards (composting 
avoids CH 4 emissions), and higher than landfilling for yard trimmings (landfilling is 
credited with the carbon storage that results from incomplete decomposition of yard 
trimmings). Overall, given the uncertainty in the analysis, the emission factors for 
composting or combusting these materials are similar. 

• The net GHG emissions from combustion of mixed MSW are lower than landfilling 
mixed MSW (under national average conditions for landfill gas recovery). Combustors 
and landfills manage a mixed waste stream; therefore, net emissions are determined more 
by technology factors (e.g., the efficiency of landfill gas collection systems and 
combustion energy conversion) than by material specificity. Material-specific emissions 
for landfills and combustors provide a basis for comparing these options with source 
reduction, recycling, and composting. 


ES-13 


Exhibit ES-4 

Net GHG Emissions from Source Reduction and MSW Management Options 

(MTCE/Ton) a _____ 


Material 

Source 

Reduction 13 

Recycling 

Composting 

Combustion 0 

Landfilling d 

Aluminum Cans 

-2.24 

-3.70 

NA 

0.02 

0.01 

Steel Cans 

-0.87 

-0.49 

NA 

-0.42 

0.01 

Copper Wire 

-2.00 

-1.34 

NA 

0.01 

0.01 

Glass 

-0.16 

-0.08 

NA 

0.01 

0.01 

HDPE 

-0.49 

-0.38 

NA 

0.25 

0.01 

LDPE 

-0.62 

-0.46 

NA 

0.25 

0.01 

PET 

-0.57 

-0.42 

NA 

0.30 

0.01 

Corrugated Cardboard 

-1.52 

-0.85 

NA 

-0.18 

0.11 

Magazines/Third-class Mail 

-2.36 

-0.84 

NA 

-0.13 

-0.08 

Newspaper 

-1.33 

-0.76 

NA 

-0.20 

-0.24 

Office Paper 

-2.18 

-0.78 

NA 

-0.17 

0.53 

Phonebooks 

-1.72 

-0.72 

NA 

-0.20 

-0.24 

Textbooks 

-2.50 

-0.85 

NA 

-0.17 

0.53 

Dimensional Lumber 

-0.55 

-0.67 

NA 

-0.21 

-0.13 

Medium-density Fiberboard 

-0.60 

-0.67 

NA 

-0.21 

-0.13 

Food Discards 

NA 

NA 

-0.05 

-0.05 

0.20 

Yard Trimmings 

NA 

NA 

-0.05 

-0.06 

-0.06 

Mixed Paper 






Broad Definition 

NA 

-0.96 

NA 

-0.18 

0.09 

Residential Definition 

NA 

-0.96 

NA 

-0.18 

0.07 

Office Paper Definition 

NA 

-0.93 

NA 

-0.16 

0.13 

Mixed Metals 

NA 

-1.43 

NA 

-0.29 

0.01 

Mixed Plastics 

NA 

-0.41 

NA 

0.27 

0.01 

Mixed Recyclables 

NA 

-0.79 

NA 

-0.17 

0.04 

Mixed Organics 

NA 

NA 

-0.05 

-0.05 

0.06 

Mixed MSW as Disposed 

NA 

NA 

NA 

-0.03 

0.12 

Carpet 

-1.09 

-1.96 

NA 

0.11 

0.01 

Personal Computers 

-15.13 

-0.62 

NA 

-0.05 

0.01 

Clay Bricks 

-0.08 

NA 

NA 

NA 

0.01 

Concrete 

NA 

0.00 

NA 

NA 

0.01 

Fly Ash 

NA 

-0.24 

NA 

NA 

0.01 

Tires 

-1.09 

-0.50 e 

NA 

0.05 

0.01 


Note that totals may not add due to rounding, and more digits may be displayed than are significant. 

NA: Not applicable, or in the case of composting of paper, not analyzed. 

a MTCE/ton: Metric tons of carbon equivalent per short ton of material. Material tonnages are on an as-managed (wet 
weight) basis. 

b Source reduction assumes initial production using the current mix of virgin and recycled inputs. 
c Values are for mass burn facilities with national average rate of ferrous recovery. 
d Values reflect estimated national average CH 4 recovery in year 2003. 
e Recycling of tires, as modeled in this analysis, consists only of retreading the tires. 


ES-14 










Exhibit ES-5 

GHG Emissions of MSW Management Options Compared to Landfilling (MTCE/Ton) a 
_ (Management Option Net Emissions Minus Landfilling Net Emissions) _ 


Material 

Source 

Reduction 6 

(Current 

Mix) 

Source 

Reduction 

(100% 

Virgin 

Inputs) 

Recycling 

Composting c 

Combustion 6 

Aluminum Cans 

-2.26 

-4.28 

-3.71 

NA 

0.01 

Steel Cans 

-0.88 

-1.02 

-0.50 

NA 

-0.43 

Copper Wire 

-2.01 

-2.03 

-1.35 

NA 

0.00 

Glass 

-0.17 

-0.19 

-0.09 

NA 

0.00 

HDPE 

-0.50 

-0.55 

-0.39 

NA 

0.24 

LDPE 

-0.63 

-0.65 

-0.47 

NA 

0.24 

PET 

-0.58 

-0.60 

-0.43 

NA 

0.28 

Corrugated Cardboard 

-1.63 

-2.32 

-0.96 

NA 

-0.29 

Magazines/Third-class Mail 

-2.28 

-2.36 

-0.76 

NA 

-0.05 

Newspaper 

-1.09 

-1.39 

-0.52 

NA 

0.03 

Office Paper 

-2.71 

-2.79 

-1.31 

NA 

-0.70 

Phonebooks 

-1.49 

-1.49 

-0.49 

NA 

0.03 

Textbooks 

-3.03 

-3.11 

-1.38 

NA 

-0.70 

Dimensional Lumber 

-0.42 

-0.42 

-0.54 

NA 

-0.08 

Medium-density Fiberboard 

-0.47 

-0.47 

-0.54 

NA 

-0.08 

Food Discards 

NA 

NA 

NA 

-0.25 

-0.25 

Yard Trimmings 

NA 

NA 

NA 

0.01 

0.00 

Mixed Paper 






Broad Definition 

NA 

NA 

-1.06 

NA 

-0.27 

Residential Definition 

NA 

NA 

-1.03 

NA 

-0.25 

Office Paper Definition 

NA 

NA 

-1.06 

NA 

-0.29 

Mixed Metals 

NA 

NA 

-1.44 

NA 

-0.30 

Mixed Plastics 

NA 

NA 

-0.42 

NA 

0.26 

Mixed Recyclables 

NA 

NA 

-0.83 

NA 

-0.20 

Mixed Organics 

NA 

NA 

NA 

-0.12 

-0.12 

Mixed MSW as Disposed 

NA 

NA 

NA 

NA 

-0.15 

Carpet 

-1.10 

-1.10 

-1.97 

NA 

0.10 

Personal Computers 

-15.14 

-15.14 

-0.63 

NA 

-0.06 

Clay Bricks 

-0.09 

-0.09 

-0.01 

NA 

-0.01 

Concrete 

-0.01 

-0.01 

-0.01 

NA 

-0.01 

Fly Ash 

-0.01 

-0.01 

-0.25 

NA 

-0.01 

Tires 

-1.10 

-1.10 

-0.51 e 

NA 

0.04 


Note that totals may not add due to rounding, and more digits may be displayed than are significant. 

NA: Not applicable, or in the case of composting of paper, not analyzed. 

a Values for landfilling reflect projected national average CH 4 recovery in year 2003. 

b Source reduction assumes initial production using the current mix of virgin and recycled inputs. 

c Calculation is based on assuming zero net emissions for composting. 

d Values are for mass burn facilities with national average rate of ferrous recovery. 

e Recycling of tires, as modeled in this analysis, consists only of retreading the tires. 


ES-15 









The ordering of combustion, landfilling, and composting is affected by (1) the GHG inventory 
accounting methods, which do not count C0 2 emissions from sustainable biogenic sources/' but do count 
emissions from sources such as plastics; and (2) a series of assumptions on sequestration, future use of 
CH 4 recovery systems, system efficiency for landfill gas recovery, ferrous metal recovery, and avoided 
utility fossil fuels. On a site-specific basis, the ordering of results between a combustor and a landfill 
could be different from the ordering provided here, which is based on national average conditions. 

EPA conducted sensitivity analyses to examine the GHG emissions from landfilling under 
varying assumptions about ( 1 ) the percentage of landfilled waste sent to landfills with gas recovery, and 
(2) CH 4 oxidation rate and gas collection system efficiency. The sensitivity analyses demonstrate that the 
results for landfills are very sensitive to these factors, which are site-specific. 3 " Thus, using a national 
average value when making generalizations about emissions from landfills masks some of the variability 
that exists from site to site. 

The scope of this report is limited to developing emission factors that can be used to evaluate 
GHG implications of solid waste decisions. EPA does not analyze policy options in this report. 
Nevertheless, the differences in emission factors across various waste management options are 
sufficiently large as to imply that GHG mitigation policies in the waste sector can make a significant 
contribution to U.S. emission reductions. A number of examples, using the emission factors in this 
report, illustrate this point. 

• At the firm level, targeted recycling programs can reduce GHGs. For example, a commercial 
facility that shifts from (a) a baseline practice of landfilling (in a landfill with no gas collection 
system) 50 tons office paper and 4 tons of aluminum cans to (b) recycling the same materials can 
reduce GHG emissions by more than 100 MTCE. 

• At the community level, a city of 100,000 with average waste generation (4.5 lbs/day per capita), 
recycling (30 percent), and baseline disposal in a landfill with no gas collection system could 
increase its recycling rate to 40 percent—for example, by implementing a pay-as-you-throw 
program—and reduce emissions by more than 3,400 MTCE per year. (Note that further growth 
in recycling would be possible; some communities already are exceeding recycling rates of 50 
percent). 

• A city of 1 million, disposing of 650,000 tons per year in a landfill without gas collection, could 
reduce its GHG emissions by about 260,000 MTCE per year by managing waste in a mass bum 
combustor unit. 

• A town of 50,000 people landfilling a total of 30,000 tons per year could install a landfill gas 
recovery system with electricity generation and reduce emissions by about 13,500 MTCE per 
year. 

• At the national level, if the United States attains the goal of a 35 percent recycling rate by 2008, 
emissions will be nearly 59 million MTCE per year lower than if no recycling took place. 


29 Sustainable biogenic sources include paper and wood products from sustainably managed forests. When these 
materials are burned or aerobically decomposed to C0 2 , the C0 2 emissions are not counted. The approach to 
measuring GHG emissions from biogenic sources is described in detail in Chapter 1. 

30 For details on the sensitivity analyses, see section 6.5 and Exhibits 6-7 and 6-8. 


ES-16 



ES.7 


OTHER LIFE-CYCLE GHG ANALYSES AND TOOLS 


Life-cycle analysis is being used increasingly to quantify the GHG impacts of private and public 
sector decisions. In addition to the life-cycle analyses that underpin the emission factors in this report, 
Environmental Defense,' 1 ICLEI, Ecobilan, and others have analyzed the life-cycle environmental 
impacts of various industry processes (e.g., manufacturing) and private and public sector practices (e.g., 
waste management). In many cases, the results of life-cycle analyses are packaged into software tools 
that distill the information according to a specific user’s needs. 

ICF International worked with EPA to create the WARM, ReCon, and DGC tools, in addition to 
researching and writing this report, and creating the emission factors used here and in the tools. As 
mentioned earlier, WARM was designed as a tool for waste managers to weigh the GHG and energy 
impacts of their waste management practices. As a result, the model focuses exclusively on waste sector 
GHG emissions, and the methodology used to estimate emissions is consistent with international and 
domestic GHG accounting guidelines. Life-cycle tools designed for broader audiences necessarily 
include other sectors and/or other environmental impacts, and are not necessarily tied to the 
Intergovernmental Panel on Climate Change (IPCC) guidelines for GHG accounting or the methods used 
in the Inventory ofU.S. Greenhouse Gas Emissions and Sinks. 

• WARM is an EPA model that enables users to input several key variables (e.g., landfill gas 
collection system information, electric utility fuel mix, and transportation distances). 32 The 
model covers 34 types of materials and five waste management options: source reduction, 
recycling, combustion, composting, and landfilling. WARM accounts for upstream energy and 
nonenergy emissions, transportation distances to disposal and recycling facilities, carbon 
sequestration, and utility offsets that result from landfill gas collection and combustion. The tool 
provides participants in DOE’s 1605(b) program with the option to report results by year, by gas, 
and by year and gas (although under 1605(b)’s revised guidelines, avoided emissions from 
recycling must be reported separately under “other indirect emissions” and not included in the 
main corporate inventory). WARM software is available free of charge in both a Web-based 
calculator format and a Microsoft® Excel spreadsheet. The tool is ideal for waste planners 
interested in tracking and reporting voluntary GHG emission reductions from waste management 
practices and for comparing the climate change impacts of different approaches. To access the 
tool, visit: http://www.epa.gov/mswclimate, then follow link to Tools. 

• Recycled Content (ReCon) Tool was created by EPA to help companies and individuals estimate 
life-cycle GHG emissions and energy impacts from purchasing and/or manufacturing materials 
with varying degrees of postconsumer recycled content. The tool covers 17 material types and an 
analysis of baseline and alternative recycled-content scenarios. ReCon accounts for total 
“upstream” GHG emissions based on manufacturing processes, carbon sequestration, and avoided 
disposal that are related to the manufacture of the materials with recycled content. ReCon also 
accounts for the total energy (based on manufacturing processes and avoided disposal) related to 
the manufacture of materials with recycled content. The tool is ideal for companies and 
individuals who want to calculate GHG emissions and energy consumption associated with 
purchasing and manufacturing using baseline and alternate recycled-content scenarios. To access 
the tool, visit: http://www.epa.gov/mswclimate, then follow link to Tools. 


31 Blum, L., Denison, R.A., and Ruston, V.F. 1997. A Life-Cycle Approach to Purchasing and Using 
Environmentally Preferable Paper: A Summary of the Paper Task Force Report,” Journal of Industrial Ecology>. 
1:3:15-46. Denison, R.A. 1996. “Environmental Life-Cycle Comparison of Recycling, Landfilling, and Incineration: 
A Review of Recent Studies”; Annual Review of Energy and the Environment 21:6:191-237. 

32 Microsoft Excel and Web-based versions of this tool are available online at the following website: 

http://www.epa.gov/globalwarming/actions/waste/tools.html. 


ES-17 





• Durable Goods Calculator (DGC) is an EPA model that enables users to calculate the GHG 
emission and energy implications for various disposal methods of durable goods. The model 
covers 14 types of durable goods and three waste management options: recycling, landfilling, and 
combustion. The Durable Goods Calculator was developed for individuals and companies that 
want to make an informed decision on the GHG and energy impact of disposing of durable 
household goods. To access the tool, visit: http://www.epa.gov/mswclimate, then follow link to 
Tools. 

• ICLEI Cities for Climate Protection (CCP) Campaign Greenhouse Gas Emission Software was 
developed by Torrie Smith Associates for ICLEI. This Windows™-based tool, targeted for use 
by local governments, can analyze emissions and emission reductions on a community-wide basis 
and for municipal operations alone. The community-wide module looks at residential, 
commercial, and industrial buildings; transportation activity; and community-generated waste. 
The municipal operations module looks at municipal buildings, municipal fleets, and waste from 
municipal in-house operations. In addition to computing GHG emissions, the CCP software 
estimates reductions in criteria air pollutants, changes in energy consumption, and financial costs 
and savings associated with energy use and other emission reduction initiatives. A version of the 
software program was made available for use by private businesses and institutions during the 
summer of 2001. CCP software subscriptions, including technical support, are available to 
governments participating in the program. For more information, visit: http://www.iclei.org/ or 
contact the U.S. ICLEI office at 510- 844-0699, iclei_usa@iclei.org. 

• The MSW Decision Support Tool (DST) and life-cycle inventory database for North America 
have been developed through funding by ORD through a cooperative agreement with the 
Research Triangle Institute (CR823052). The methodology is based on a multimedia, 
multipollutant approach and includes analysis of GHG emissions as well as a broader set of 
emissions (air, water, and waste) associated with MSW operations. The MSW-DST is available 
for site-specific applications and has been used to conduct analyses in several states and 15 
communities, including use by the U.S. Navy in the Pacific Northwest. The tool is intended for 
use by solid waste planners at state and local levels to analyze and compare alternative MSW 
management strategies with respect to cost, energy consumption, and environmental releases to 
the air, land, and water. The costs are based on full cost accounting principles and account for 
capital and operating costs using an engineering economics analysis. The MSW-DST calculates 
not only projected emissions of GHGs and criteria air pollutants, but also emissions of more than 
30 air- and water-borne pollutants. The DST models emissions associated with all MSW 
management activities, including waste collection and transportation, transfer stations, materials 
recovery facilities, compost facilities, landfills, combustion and refuse-derived fuel facilities, 
utility offsets, material offsets, and source reduction. The differences in residential, multifamily, 
and commercial sectors can be evaluated individually. The software has optimization capabilities 
that enable one to identify options that evaluate minimum costs as well as solutions that can 
maximize environmental benefits, including energy conservation and GHG reductions. 

At the time of the publication of this report, the LCI database for North America was expected to 
be released in early- to mid-2006. The DST will be available on the Web. The MSW-DST 
provides extensive default data for the full range of MSW process models and requires minimum 
input data. However, these defaults can be tailored to the specific communities using site-specific 
information. The MSW-DST also includes a calculator for source reduction and carbon 
sequestration using a methodology that is consistent with the IPCC in terms of the treatment of 
biogenic C0 2 emissions. For more information, refer to the project website: http:// www.rti.org/ . 
then search the tenn “DST,” or contact Keith Weitz, Research Triangle Institute, 919-541-6973, 
kaw@rti.org . 


ES-18 





Comparison of EPA/ORD and EPA/OSW Emission Factors 

An effort to harmonize previous life-cycle emission factors with the results of work by EPA’s 
Office of Research and Development (ORD) was conducted in October 2000. Noticing significant 
differences in our bottom line emission factors, EPA compared a range of assumptions, including energy 
consumption, fuel mix, loss rates, landfill oxidation rate, timing of landfill methane emissions, fraction of 
landfill gas collected, electricity mix, transportation distances, and carbon storage. The comparison of 
energy intensities and fuel mixes included process and transportation energy for virgin and recycled 
production of each material type. Because the previous Office of Solid Waste (OSW) energy values were 
based on an average of Franklin Associates, Ltd. (FAL) and Tellus data, EPA compared the ORD values 
to the FAL data, Tellus data, and average of FAL and Tellus data. 

This comparison revealed that the differences between the OSW and ORD emission factors are 
mostly attributable to the different assumptions about energy consumption (i.e., the sum of 
precombustion, process, and transportation energy), fuel mix, and loss rates. In general, it was found that 
ORD’s total energy values are lower than OSW’s energy values for both virgin and recycled materials. 
Comparing fuel mix, EPA found the most significant differences occurring for electricity, coal, natural 
gas, and “other” fuel types comprising process energy. The fractions of diesel fuel, residual fuel, and 
natural gas exhibited the greatest disparities for transportation energy. The comparison of loss rates, 
which are used to develop the recycling emission factors, showed significant variation for office paper, 
steel cans, and, to a lesser extent, newspaper. 

In an effort to reconcile the remaining differences between ORD and OSW estimates of GHG 
emissions from the acquisition of raw materials and their manufacture into products, EPA identified 
additional methodological differences that could be affecting the recycling numbers. In particular, EPA 
found that ORD simulates closed-loop recycling for all materials, while OSW assumes open-loop 
recycling for office paper and corrugated cardboard. EPA also found that ORD’s estimates do not include 
non-energy process emissions from perfluorocarbons (PFCs). To isolate any remaining differences 
between the two analyses, EPA substituted ORD energy intensities, fuel mixes, and loss rates into the 
OSW model. 

Once all methodological differences between ORD and OSW estimates for raw materials 
acquisition and manufacturing had been identified and resolved, EPA selected the material types for 
which ORD data could be substituted for the existing OSW data: glass, HDPE, LDPE, PET, corrugated 
cardboard, magazines/third-class mail, newspaper, office paper, phonebooks, and textbooks. For wood 
products, ORD did not develop emission factors, while for steel its data was not sufficiently 
disaggregated to replace the existing OSW data. 


• The Tool for Environmental Analysis and Management (TEAM), developed by Ecobilan, 
simulates operations associated with product design, processes, and activities associated with 
several industrial sectors. The model considers energy consumption, material consumption, 
transportation, waste management, and other factors in its evaluation of environmental impacts. 
For more information, visit: http://www.ecobalance.com/uk team.php . 

ES.8 LIMITATIONS OF THE ANALYSIS 

When conducting this analysis, EPA used a number of analytical approaches and numerous data 
sources, each with its own limitations. In addition, EPA made and applied assumptions throughout the 
analysis. Although these limitations would be troublesome if used in the context of a regulatory 
framework, EPA believes that the results are sufficiently accurate to support their use in voluntary 
programs. Some of the major limitations include the following: 

• The manufacturing GHG analysis is based on estimated industry averages for energy usage, and 
in some cases the estimates are based on limited data. In addition, EPA used values for the 
average GHG emissions per ton of material produced, not the marginal emission rates per 
incremental ton produced. In some cases, the marginal emission rates may be significantly 
different. 


ES-19 




• The forest carbon sequestration analysis deals with a very complicated set of interrelated 
ecological and economic processes. Although the models used represent the state-of-the-art in 
forest resource planning, their geographic scope is limited. Because of the global market for 
forest products, the actual effects of paper recycling would occur not only in the United States but 
in Canada and other countries. Other important limitations include: (1) the model assumes that 
no forested lands will be converted to nonforest uses as a result of increased paper recycling; and 
(2) EPA uses a point estimate for forest carbon sequestration, whereas the system of models 
predicts changing net sequestration over time. 

• The composting analysis considers a small sampling of feedstocks and a single compost 
application (i.e., agricultural soil). The analysis did not consider the full range of soil 
conservation and management practices that could be used in combination with compost and their 
impacts on carbon storage. 

• The combustion analysis uses national average values for several parameters; variability from site 
to site is not reflected in the estimate. 

• The landfill analysis (1) incorporates some uncertainty on CH 4 generation and carbon 
sequestration for each material type, due to limited data availability; and (2) uses estimated CH 4 
recovery levels for the year 2003 as a baseline. 

Finally, throughout most of the report, EPA expresses analytical inputs and outputs as point 
estimates. EPA recognizes that a rigorous treatment of uncertainty and variability would be useful, but in 
most cases the information needed to treat these in statistical terms is not available. The report includes 
some sensitivity analyses to illustrate the importance of selected parameters and expresses ranges for a 
few other factors such as GHG emissions from manufacturing. EPA encourages readers to provide more 
accurate information where it is available; perhaps with additional information, future versions of this 
report will be able to shed more light on uncertainty and variability. Meanwhile, EPA.cautions that the 
emission factors reported here should be evaluated and applied with an appreciation for the limitations in 
the data and methods, as described at the end of each chapter. 


ES-20 


1. LIFE-CYCLE METHODOLOGY 


This report is the third edition of Solid Waste Management and Greenhouse Gases: A Life-Cycle 
Assessment of Emissions and Sinks. EPA made the following improvements to the second edition of the 
report: 

• Developed emission factors for seven new material types: copper wire, clay bricks, concrete, fly 
ash, tires, carpet, and personal computers; 

• Incorporated new energy data into calculations of electric utility offsets; 

• Revised carbon coefficients and fuel use for national average electricity generation; 

• Updated information on landfill gas recovery rates to reflect the latest values from the Inventory 
ofU.S. Greenhouse Gas Emissions and Sinks ; 

• Added a discussion of emerging issues in the area of climate change and waste management; 

• Provided a revised list of suggested proxy values for voluntary reporting of GHG emission 
reductions; 

• Added a discussion of open-loop recycling, as it relates to emission factors for fly ash, carpet, 
personal computers, and mixed paper; 

• Included emissions from retail transport in the methodology; 

• Updated the current mix of postconsumer recycled content for various materials; and 

• Updated the analysis of forest carbon sequestration and moved the discussion to the recycling 
chapter. 

All of these changes and/or revisions are described in more detail throughout the body of the report. 

In this edition of the report, EPA has moved some of the background information from the body 
of the report to separate background documents to improve clarity. 1 The technical details remain 
available to the interested, while keeping the main body of this report straightforward. Background 
Document A: A Life Cycle of Process and Transportation Energy for Eight Different Materials provides 
data on life-cycle energy intensity and fuel mix, provided by Franklin Associates, Ltd. (FAL). 
Background Document B: Methodology for Estimating the Amounts and Types of Energy Consumed in 
Raw Materials Acquisition and Manufacturing of Eight Different Materials provides a discussion of the 
review cycles leading up to the first and second editions of the report. Background Document C: Review 
Process for the Report includes a discussion of how the EPA researchers screened materials for the first 
edition of the report. Background Document D: Comment-Response Document presents comments and 
responses given during expert review of the first edition of the report. In addition to these four 
background documents, there are several material-specific background documents that explain how EPA 
developed specific emission factors for materials new to this edition of the report: copper wire, concrete, 
clay bricks, fly ash, tires, carpet, and personal computers. 2 


1 Available at EPA, Global Wanning—Waste, “Solid Waste Management and Greenhouse Gases.” Go to: 
http://www.epa.gov/mswclimate, then follow links to Publications -> Reports, Papers, and Presentations -> This 
report -> Background Documents. 

2 These four background documents all have the same beginning to their titles: Background Document for Life- 
Cycle Greenhouse Gas Emission Factors for (1) Clay Brick Reuse and Concrete Recycling , (2) Fly Ash Used as a 


1 






The remainder of this chapter provides an overview of the methodology used to calculate the 
GHG emissions associated with various management strategies for MSW. The first section briefly 
describes the life-cycle framework used for the analysis. Next is a discussion of the materials included in 
the analysis. The final three sections present a description of key inputs and baselines, a summary of the 
life-cycle stages, and an explanation of how to estimate and compare net GHG emissions and sinks. 

1.1 THE OVERALL FRAMEWORK: A STREAMLINED LIFE-CYCLE INVENTORY 

Early in this analysis of the GHG benefits of specific waste management practices, it became 
clear that all waste management options provide opportunities for reducing GHG emissions, depending on 
individual circumstances. Although source reduction and recycling are often the most advantageous 
waste management practices from a GHG perspective, a material-specific comparison of all available 
waste management options clarifies where the greatest GHG benefits can be obtained for particular 
materials in MSW. A material-specific comparison can help waste managers and policymakers identify 
the best options for GHG reductions through alternative waste management practices. 

This study determined that the best way to conduct such a comparative analysis is a streamlined 
application of a life-cycle assessment (LCA). A full LCA is an analytical framework for understanding 
the material inputs, energy inputs, and environmental releases associated with manufacturing, using, and 
disposing of a given material. A full LCA generally consists of four parts: (1) goal definition and 
scoping; (2) an inventory of the materials and energy used during all stages in the life of a product or 
process, and an inventory of environmental releases throughout the product life cycle; (3) an impact 
assessment that examines potential and actual human health effects related to the use of resources and 
environmental releases; and (4) an assessment of the change that is needed to bring about environmental 
improvements in the product or processes. 

A full LCA is beyond the scope of this analysis. Rather, the streamlined LCA described in this 
report is limited to an inventory of the emissions and other environmental impacts related to global 
warming. This study did not assess human health impacts, necessary environmental improvements, and 
air, water, or environmental impacts that do not have a direct bearing on climate change. This analysis 
also simplifies the calculation of emissions from points in the life cycle that occur before a material is 
discarded. For a more extensive explanation of this “waste generation” reference point, see Section 1.5, 
below. 

1.2 MSW MATERIALS CONSIDERED IN THE STREAMLINED LIFE-CYCLE 

INVENTORY 

Each material in MSW has different GHG impacts depending on how it is manufactured and 
disposed of at the end of its useful life. EPA’s research into these impacts began with a screening analysis 
of 37 of the most common materials and products found in MSW. * * 3 The materials included in screening 
analysis then were ranked by their potential for GHG reductions. 4 The second edition of the report 


Cement Replacement in Concrete , (3) Carpet and Personal Computers, and (4) Copper Wire. These are available at 

the EPA’s Global Wanning—Waste, “Solid Waste Management and Greenhouse Gases” website. Op cit. 

3 In addition to the materials and products covered in the report, the screening analysis included the following 
materials and products: other paper materials (bags and sacks, other paper packaging, books, other paperboard 
packaging, wrapping papers, paper plates and cups, folding cartons, other nonpackaging paper, and tissue paper and 
towels), other plastic materials (plastic wraps, plastic bags and sacks, other plastic containers, and other plastic 
packing), other metal materials (aluminum foil/closures, other steel packaging), and other miscellaneous materials 
(miscellaneous durable goods, wood packaging, furniture and furnishings, and other miscellaneous packaging). 

4 For more information on the screening analysis used to identify materials for the first edition of the report, see 
Background Document C, available at the EPA, Global Warming—Waste, “Background Documents for Solid 
Waste Management and GHG Report” website. Op cit. 


2 



included 16 materials: aluminum cans, steel cans," glass, high-density polyethylene (HDPE) plastic blow- 
molded containers, low-density polyethylene (LDPE) plastic blow-molded containers, polyethylene 
terephthalate (PET) plastic blow-molded containers, corrugated cardboard, newspaper, office paper, 5 6 
magazines and third-class mail, phonebooks, textbooks, dimensional lumber, medium-density fiberboard, 
food discards, and yard trimmings. In addition to these materials, EPA examined the GHG implications of 
various management strategies for, mixed MSW, mixed plastics, mixed organics, mixed recyclables, and 
three grades of mixed paper (broad, residential, and office). Most of the changes between the second and 
third editions of this report reflect additions of new or updated data. This third edition features a further 
expanded list of material types, including copper wire, clay bricks, concrete, fly ash, tires, and two 
composite materials: carpet and personal computers. Some of these new materials require a different 
approach than has been used in previous editions of the report. For more details on the methodology used 
to evaluate any of these new materials, please see the Background Documents. 7 

In this edition of the report, EPA has added emission factors for several new material types as described 
below: 

• Copper Wire —copper wire was added to broaden the range of materials for which there are 
emission factors. Life-cycle data for copper wire were obtained in part from research on personal 
computers and their raw material inputs. 

• Clay Brick —this material is analyzed for only two management options: source reduction (i.e. 
reuse of bricks) and landfilling. EPA research indicates that there is very little postconsumer 
recycling of bricks. Likewise, almost all bricks in this country are made from virgin materials, so 
EPA has not analyzed the impacts of using recycled material in brick manufacture. 

• Concrete —in this context, concrete is recycled in a semiopen loop. EPA researchers analyzed 
concrete that is crushed and used in place of virgin aggregate (sand, gravel, etc.) in the 
manufacture of new concrete. It replaces virgin aggregate, not virgin concrete, although 
aggregate is used to create concrete. 

• Fly Ash —as a byproduct of coal combustion, source reduction of fly ash is not considered to be a 
viable waste management option. Instead, EPA has modeled recycling of fly ash in an open loop 
for the purpose of displacing Portland cement in the production of concrete. 

• Tires —tires were added as a material type due to the large number disposed in the United States 
every year. EPA has modeled the recycling of tires based on retreading and the combustion of 
tires based on their use as a tire-derived fuel (TDF). 

• Carpet —carpet is a composite, meaning that recycling is necessarily more complicated than for 
single material products (like steel cans). For this analysis, EPA researchers considered only 
nylon broadloom residential carpet. Carpet consists of carpet fiber (nylon), carpet backing 
(usually polypropylene), and synthetic-latex-and-limestone adhesive. In this analysis, carpet is 
recycled only in an open-loop process, into carpet pad, carpet backing, and molded auto parts. 
Source reduction for carpet consists of making caipets thinner, or procedures to make 
replacement less frequent (e.g., cleaning and upkeep). 


5 Other steel materials also may be recycled, but this analysis was limited to steel cans from households. 

6 Office paper refers to the type of paper used in computer printers and photocopiers. 

7 These are available at the EPA’s Global Warming—Waste, “Solid Waste Management and Greenhouse Gases” 
website. Op cit. 


3 



• Personal Computers —PCs are also a composite and are a complex combination ot many types 

of material; by weight the main components are plastics, glass, lead, steel, copper, and aluminum. 
PCs are recycled in an open-loop process; this report analyzes the production of asphalt, CRT 
(cathode ray tube) glass, lead bullion, steel sheet, copper wire, and aluminum sheet from recycled 
PCs. Source reduction of PCs includes finding ways to make PCs last longer. 

This edition of the report also incorporates data developed by ORD through its work on life-cycle 
management of MSW. ORD’s dataset on energy and fuel mix was thoroughly reviewed by industry and 
other stakeholders, and was more up-to-date than some of the information in the first edition of this 
report. Thus, where a complete set of energy intensity and fuel mix data was available from ORD, that 
information was incorporated into the second edition of this report. For other materials—steel cans and 
mixed paper (broad, residential, and office definitions)—EPA retained the original dataset developed by 
FAL. This edition includes data (also developed by FAL) on dimensional lumber and medium-density 
fiberboard. Exhibit 1-1 lists the materials that were analyzed for this report and the energy-related data 
sources underlying the estimates. All of the material types listed in Exhibit 1-1 are discussed in 
subsequent chapters and included in exhibits throughout the report, with the exception of three mixed 
waste categories. Mixed plastics, mixed recyclables, and mixed organics are included only in Chapter 7 
because emission factors for these materials simply reflect the weighted average emissions of other 
material types. 


Exhibit 1-1 Materials Analyzed and Energy-related Data Sources 


Material 

Energy Data Source 

Material 

Energy Data Source 

Aluminum Cans 

FAL 

Clay Bricks 

Athena 3 

Steel Cans 

FAL 

Concrete 

USCB; USGS 9 

Copper Wire 

FAL; Battelle 10 

Fly Ash 

PCA * 11 

Glass 

ORD 

Tires 

CIEEDAC; AG 12 

Corrugated Cardboard 

ORD 

Carpet 

FAL 

Magazines/Third-class Mail 

ORD 

Personal Computers 

FAL 

Newspaper 

ORD 

Mixed Paper 


Office Paper 

ORD 

Broad Definition 13 

FAL 

Phonebooks 

ORD 

Residential Definition 

FAL 

Textbooks 

ORD 

Office Paper Definition 

FAL 

Dimensional Lumber 

FAL 

Mixed Plastics 

Weighted Average 

Med.-density Fiberboard 

FAL 

Mixed Recyclables 

Weighted Average 

Food Discards 

NA 

Mixed Organics 

NA 

Yard Trimmings 

NA 

Mixed MSW 

NA 


NA = Not applicable (data not energy-related) 


8 Athena Sustainable Materials Institute, 1998, life-cycle research. 

9 U.S. Census Bureau, 1997 Economic Census; and Aggregates from Natural and Recycled Sources, a U.S. 
Geological Survey Circular by David Wilburn and Thomas Goonan. 

10 Battelle, 1975. Energy Use Patterns in Metallurgical and Nonmetallic Mineral Processing (Phase 4), Battelle 
Columbus Laboratories - U.S. Bureau of Mines. 1975. 

11 Portland Cement Association’s (PCA) U.S. Industry Fact Sheet, 2003 Edition ; the 2000 PCA report 
Environmental Life Cycle Inventory of Portland Cement Concrete by Nisbet, et al.; and the IPCC Revised 1996 
Guidelines for National Greenhouse Gas Inventories. 

12 Canadian Industrial End-Use Energy Data and Analysis Center. Available online at: 

www.deh.gov.au/settlements/publications/waste/tvres/national-approach/ : Atech Group, “A National Approach to 
Waste Tyres.” Prepared for Environment Australia, June 2001. Available online at: 
www.deh.gov.au/settlements/publications/waste/tvres/national-approach/ . 

13 For the composition of these three categories of mixed paper, please see Exhibit 3-2. 


4 









1.3 


KEY INPUTS FOR THE STREAMLINED LIFE-CYCLE INVENTORY 


Evaluating the GHG emissions of waste management requires analysis of three factors: (1) GHG 
emissions throughout the life cycle of the material (including the chosen disposal option); (2) the extent to 
which carbon sinks are affected by manufacturing and disposing of the material; and (3) the extent to 
which the management option recovers energy that can be used to replace electric utility energy, thus 
reducing utility GHG emissions. 

GHG Emissions Relevant to Waste : The most important GHGs for purposes of analyzing MSW 
management options are carbon dioxide (CO : ), methane (CH 4 ), nitrous oxide (N 2 0), and 
perfluorocarbons (PFCs). Of these, C0 2 is by far the most common GHG emitted in the United States. 
Most C0 2 emissions result from energy use, particularly fossil fuel combustion. A great deal of energy is 
consumed when a product is manufactured and then discarded. This energy is used in the following 
stages: (1) extracting and processing raw materials; (2) manufacturing products; (3) managing products at 
the end of their useful lives; and (4) transporting materials and products from one life-cycle stage to 
another. This study estimated energy-related GHG emissions during all of these stages, except for 
transportation of products from retailers to consumers (because GHG emissions resulting from 
transportation to consumers will vary little among the options considered). Much of this report is devoted 
to explaining the methodology employed for quantifying the energy used—and the resulting C0 2 
emissions—at each stage in the life cycle of any given material in MSW. Energy consumed in connection 
with consumer use of products is not evaluated, because it is assumed that energy use for the selected 
materials would be about the same whether the product is made from virgin or recycled inputs. In 
addition, energy use at this life-cycle 
stage is small (or zero) for all materials 
studied except personal computers. 

CH 4 , a more potent GHG, is 
produced when organic waste 
decomposes in an oxygen-free 
(anaerobic) environment, such as a 
landfill. CH 4 from landfills is the largest 
source of CH 4 in the United States; 14 
these emissions are addressed in Chapter 
6. CH 4 is also emitted when natural gas 
is released to the atmosphere during 
production of coal or oil, production or 
use of natural gas, and agricultural 
activities. 

N 2 0 results from the use of 
commercial and organic fertilizers and 
fossil fuel combustion, as well as other 
sources. This analysis estimated N 2 0 
emissions from waste combustion. 

PFCs (tetrafluoromethane (CF 4 ) 
and hexafluoroethane (C 2 F 6 )) are emitted 
during the reduction of alumina to aluminum in the primary smelting process. The source of fluorine for 
CF 4 and C 2 F 6 is the molten cryolite (Na 3 AlF 6 ) where the reduction of alumina occurs. PFCs are formed 
when the fluorine in cryolite reacts with the carbon in the anode (a carbon mass of paste, coke briquettes, 


14 EPA. 2005. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2003. U.S. Environmental Protection 
Agency, Office of Policy, Planning and Evaluation, Washington, DC. EPA-430-R-05-003. 


Comparing GHGs 

C0 2 , CH 4 , N 2 0, and PFCs are very different gases in 
terms of their heat-trapping potential. An international 
protocol has established C0 2 as the reference gas for 
measurement of heat-trapping potential (also known as global 
warming potential or GWP). By definition, the GWP of 
1 kilogram (kg) of C0 2 is 1. 

CH 4 has a GWP of 21, which means that 1 kg of CH 4 
has the same heat-trapping potential as 21 kg of C0 2 . 

N 2 0 has a GWP of 310. 

PFCs are the most potent GHG included in this 
analysis; GWPs are 6,500 for CF 4 and 9,200 for C 2 F 6 . 

In this report, emissions of C0 2 , CH 4 , N 2 0, and PFCs 
have been converted to their “carbon equivalents.” Because 
C0 2 is 12/44 carbon by weight, 1 metric ton of C0 2 is equal to 
12/44 or 0.27 metric tons of carbon equivalent (MTCE). The 
MTCE value for 1 metric ton of each of the other gases is 
determined by multiplying its GWP by a factor of 12/44. (All 
data provided here are from the IPCC, Climate Change 1995: 
The Science of Climate Change , 1996, p. 121.) 


5 








or prebaked carbon blocks) and in the carbon lining that serves as the cathode. Although the quantities of 
PFCs emitted are small, these gases are significant because of their high global warming potential. 

Carbon Stocks, Carbon Storage, and Carbon Sequestration : This analysis includes carbon storage 
to the extent that it is due to waste management practices. Carbon storage involves taking carbon-rich 
(biogenic) waste, such as wood products, and managing it so that the carbon is stored, rather than released 
to the atmosphere through burning or decay. For example, landfilled organic materials result in landfill 
carbon storage, as carbon is moved from a product pool (e.g., furniture) to the landfill pool. The same is 
true for composted organics that lead to carbon storage in soil. 

Carbon sequestration differs from carbon storage because it represents a transfer of carbon from 
the atmosphere to a carbon pool, rather than the preservation of materials already containing carbon, as in 
landfilling. Carbon sequestration occurs when trees or other plants undergo photosynthesis, converting 
C0 2 in the atmosphere to carbon in their biomass. In this analysis, EPA considers the impact of waste 
management on forest carbon sequestration. The amount of carbon stored in forest trees is referred to as a 
forest’s carbon stock. 

The baseline against which changes in carbon stocks are measured is a projection by the U.S. 
Forest Service of forest growth, mortality, harvests, and other removals under anticipated market 
conditions for forest products. One of the assumptions for the projections is that U.S. forests will be 
harvested on a sustainable basis (i.e., trees will be grown at a rate at least equal to the rate at which they 
are cut). 15 Thus, the baseline assumes that harvesting trees at current levels results in no diminution of 
the forest carbon stock and no additional C0 2 in the atmosphere. On the other hand, forest carbon 
sequestration increases as a result of source reduction or recycling of paper products because both source 
reduction and recycling cause annual tree harvests to drop below otherwise anticipated levels (resulting in 
additional accumulation of carbon in forests). Consequently, source reduction and recycling “get credit” 
for increasing the forest carbon stock, whereas other waste management options (combustion and 
landfilling) do not. 

Although source reduction and recycling are associated with forest carbon sequestration, 
composting—in particular, application of compost to degraded soils—enhances soil carbon storage. Four 
mechanisms of increased carbon storage are hypothesized in Chapter 4; a modeling approach is used to 
estimate the magnitude of carbon storage associated with three of those mechanisms. 

Finally, landfills are another means by which carbon is removed from the atmosphere. Landfill 
carbon stocks increase over time because much of the organic matter placed in landfills does not 
decompose, especially if the landfill is located in an arid area. Flowever, not all carbon in landfills is 
counted in determining the extent to which landfills are carbon stocks. For example, the analysis does not 
count plastic in landfills toward carbon storage. Plastic in a landfill represents simply a transfer from one 
carbon stock (the oil field containing the petroleum or natural gas from which the plastic was made) to 
another carbon stock (the landfill); thus, no change has occurred in the overall amount of carbon stored. 
On the other hand, the portion of organic matter (such as yard trimmings) that does not decompose in a 
landfill represents an addition to a carbon stock, because it would have largely decomposed into C0 2 if 
left to deteriorate on the ground. 


15 Assuming a sustainable harvest in the United States is reasonable because from 1952 to 1997 U.S. forest carbon 
stocks steadily increased. In the early part of this period, the increases were mostly due to reversion of agricultural 
land to forest land. More recently, improved forest management practices and the regeneration of previously cleared 
forest areas have resulted in a net annual uptake (sequestration) of carbon. The steady increase in forest carbon 
stocks implies sustainable harvests, and it is reasonable to assume that the trend of sustainable harvests will 
continue. 


6 




Although changes in fossil fuel carbon stocks (i.e., reductions in oil field stores that result from 
the extraction and burning of oil resources) are not measured directly in this analysis, the reduction in 
fossil fuel carbon stocks is indirectly captured by counting the C0 2 emissions from fossil fuel combustion 
in calculating GHG emissions. 

Avoided Electric Utility GHG Emissions Related to Waste : Waste that is used to generate 
electricity (either through waste combustion or recovery of CH 4 from landfills) displaces fossil fuels that 
utilities would otherwise use to produce electricity. Fossil fuel combustion is the single largest source of 
GHG emissions in the United States. When waste is substituted for fossil fuel to generate electricity, the 
GHG emissions from burning the waste are offset by the avoided electric utility GHG emissions. When 
gas generated from decomposing waste at a landfill is combusted for energy, GHG emissions are reduced 
from the landfill itself, and from avoided fossil fuel use for energy. 

Reference Years : The reference year selected for most parts of the analysis is the most recent year 
for which data are available. However, for the system efficiency and ferrous recovery rate at waste 
combustors, this study uses values previously projected for the year 2000. For paper recycling, annual 
projections through 2019 were used to develop an average forest carbon storage value for the period from 
2005 through 2019. 16 The compost analysis relied on model simulations of compost application, 
beginning in 1996 and ending in 2005. The carbon storage estimates resulting from these model runs 
correspond to model outputs in 2010. The EPA researchers developed “future” 17 scenarios for paper 
recycling, composting, and carbon storage analyses because some of the underlying factors that affect 
GHG emissions are changing rapidly, and this study seeks to define relationships (e.g., between tonnage 
of waste landfilled and CH 4 emissions) that represent an average over the next several years. Some of 
these scenarios are described in more detail below. 

• When the first edition of this report was published in 1998, there were some small municipal 
waste combustors that did not recover energy. The modeling summarized in the report assumed 
that those facilities will be closed in the near future; all combustors are assumed to recover 
energy. The initial study also used an estimate provided by the combustion industry for 
anticipated levels of ferrous recovery. 

• For paper recycling, earlier analyses indicated that the marginal impact of increased paper 
recycling on forest carbon sequestration changes over time. The impact also differs depending on 
the initial paper recycling rate and how that rate changes over time. To estimate the impact of 
increased paper recycling on forest carbon sequestration, the study needed to account for these 
influences. First, EPA used the American Forest and Paper Association’s estimate of a 50 percent 
paper recycling rate in 2003. 18 The trajectory for a baseline scenario for paper recycling passes 
through 50 percent in 2000, with continued modest increases in the following years. Because of 
the need to estimate the impact of efforts (e.g., by EPA) to enhance recycling beyond the baseline 
projected rate, the researchers developed a plausible scenario for enhanced paper recycling rates 
and then compared the projected forest carbon sequestration under the baseline and increased 
recycling scenarios. 19 (This approach is fully described in Chapter 3.) 


16 The models EPA used simulated carbon sequestration through 2040, but the researchers selected a value based on 
average conditions through 2020. 

17 In the case of system efficiency and ferrous recovery at waste combustors, the year 2000 represented a future 
value when the first edition of this report was published. The 2000 values have not been updated; therefore, the 
values in this report no longer reflect future conditions. This edition of the report does not reflect these updated 
values. 

18 Actual paper recovery in 2003 (taken from EPA’s Municipal Solid Waste in the United States: 2003 Facts and 
Figures ) averaged about 48 percent, confirming that 50 percent is a reasonable approximation for 2003. 

19 Note that this estimate is necessary for analyzing the scenarios; however, it does not represent a plan of action by 
EPA. 


7 





• The landfill recovery scenario is based on estimated recovery rates and percentages of waste 
disposed in landfills with no recovery, landfills with only flaring, and landfills with landfill-gas- 
to-energy projects for the year 2004. According to the researchers' estimates, 59 percent ot all 
landfill CH 4 was generated at landfills with recovery systems, and the remaining 41 percent was 
generated at landfills without landfill gas (LFG) recovery. 2 " Of the 59 percent of all CH 4 
generated at landfills with LFG recovery, 53 percent (or 31 percent of all CH 4 ) was generated at 
landfills that use LFG to generate electricity, and 47 percent (or 28 percent of all CH 4 ) at landfills 
that flare LFG. 21 

1.4 SUMMARY OF THE LIFE-CYCLE STAGES 

Exhibit 1-2 shows the GHG sources and carbon sinks associated with the manufacture of various 
materials and the postconsumer management of these materials as wastes. As shown in the exhibit, GHGs 
are emitted from (1) the preconsumer stages of raw materials acquisition and manufacturing, and (2) the 
postconsumer stage of waste management. No GHG emissions are attributed to the consumer’s use of 
any product. 

The remainder of this chapter describes how this study analyzed each of the upstream (raw 
materials acquisition, manufacturing, and forest carbon sequestration) and downstream (source reduction, 
recycling, composting, combustion, and landfilling) stages in the life cycle. The following sections 
explain stages of the life cycle (Exhibit 1-2) and the corresponding emission factor components (Exhibit 
1-3), and outline the GHG emissions and carbon sinks associated with each stage. These GHG emissions 
and carbon sinks are described in detail and quantified for each material in Chapters 2 through 6. 

1.4.1 GHG Emissions and Carbon Sinks Associated with Raw Materials Acquisition and 
Manufacturing 

The top left comer of Exhibit 1-2 shows inputs for raw materials acquisition. These virgin inputs 
are used to make various materials, including ore for manufacturing metal products, trees for making 
paper products, and petroleum or natural gas for producing plastic products. Fuel energy also is used to 
obtain or extract these material inputs. 

The inputs used in manufacturing are (1) energy and (2) either virgin raw materials or recycled 
materials. In the exhibit, these inputs are identified with arrows that point to the icon labeled 
“Manufacturing.” 

For source reduction, the “baseline” GHG emissions from raw materials acquisition and 
manufacturing are avoided. This analysis thus estimates, for source reduction, the GHG reductions 
(relative to a baseline of initial manufacture) at the raw materials acquisition and manufacturing stages. 
Source reduction is assumed to entail more efficient use of a given material. Examples are lightweighting 
(reducing the quantity of raw material in a product), double-sided photocopying, and extension of a 
product’s useful life). In the case of clay bricks, source reduction refers to the reuse of old bricks. No 
other material substitutions are assumed for source reduction; therefore, this report does not 


20 Based on landfill CH 4 generation and collection data from the Inventory ofU.S. Greenhouse Gas Emissions and 
Sinks: 1990-2004 ), and an estimated national average landfill CH 4 recovery efficiency of 75 percent. 

21 The assumption that 53 percent of landfills recovering CH 4 use it to generate electricity is subject to change over 
time based upon changes in the cost of recovery, and the potential payback. Additionally, new technologies may 
arise that use recovered CH 4 for purposes other than generating electricity. 


8 




















Exhibit 1-3 Components of Net Emissions for Various MSW Management Strategies 


MSW 

Management 

Strategy 

GHG Sources and Sinks 

Process and Transportation 
GHGs from Raw Materials 
Acquisition and 
Manufacturing 

Forest Carbon 
Sequestration or Soil 
Carbon Storage 

Waste Management 
GHGs 

Source 

Reduction 

Decrease in GHG emissions, 
relative to the baseline of 
manufacturing 

Increase in forest carbon 
sequestration 

NA 

Recycling 

Decrease in GHG emissions due 
to lower energy requirements 
(compared to manufacture from 
virgin inputs) and avoided 
process nonenergy GHGs 

Increase in forest carbon 
sequestration 

Process and 
transportation emissions 
are counted in the 
manufacturing stage 

Composting 

No emissions/sinks 3 

Increase in soil carbon 
storage 

Compost machinery 
emissions and 
transportation emissions 

Combustion 

Baseline process and 
transportation emissions due to 
manufacture from the current 
mix of virgin and recycled inputs 

NA 

Nonbiogenic C0 2) N 2 0 
emissions, avoided utility 
emissions, and 
transportation emissions 

Landfilling 

Baseline process and 
transportation emissions due to 
manufacture from the current 
mix of virgin and recycled inputs 

NA 

CH 4 emissions, long-term 
carbon storage, avoided 
utility emissions, and 
transportation emissions 


a No manufacturing transportation GHG emissions are considered for composting of food discards and yard trimmings because 
these materials are not considered to be manufactured. 

NA = Not Applicable 


analyze any corresponding increases in production and disposal of other materials (which could result in 
GHG emissions). 22 For some materials, such as fly ash, food discards, yard trimmings, and concrete, 
source reduction was not considered a possible management strategy. 

The GHG emissions associated with raw materials acquisition and manufacturing are (1) GHG 
emissions from energy used during the acquisition and manufacturing processes, (2) GHG emissions from 
energy used to transport materials, 23 and (3) nonenergy GHG emissions resulting from manufacturing 
processes (for aluminum, steel, plastics, and office paper). Each type of emission is described below. 
Changes in carbon sequestration in forests also are associated with raw materials acquisition for paper 
products. 

Process Energy GHG Emissions : Process energy GHG emissions consist primarily of C0 2 
emissions from the combustion of fuels used in raw materials acquisition and manufacturing. C0 2 
emissions from combustion of biomass are not counted as GHG emissions. (See “C0 2 Emissions from 
Biogenic Sources” text box.) 

The majority of process energy C0 2 emissions are from the direct combustion of fuels, e.g., to 
operate ore mining equipment or to fuel a blast furnace. Fuel also is needed to extract the oil or mine the 
coal that is ultimately used to produce energy and transport those fuels to the place where they are used. 
Thus, indirect C0 2 emissions from this “precombustion energy” are counted in this category as well. 


22 Although material substitution is not quantitatively addressed in the report, it is discussed from a methodological 
standpoint in Chapter 2 and also is discussed briefly in Chapter 3, Section 3.4. 

23 For some materials (plastics, magazines/third-class mail, office paper, phonebooks, and textbooks), the 
transportation data EPA received were included in the process energy data. For these materials, EPA reports total 
GHG emissions associated with process and transportation in the “process energy” estimate. 


10 














When electricity generated by combustion of fossil fuels is used in manufacturing, the C0 2 emissions 
from the fossil fuels also are counted. 

To estimate process energy GHG emissions, the study first obtained estimates of both the total 
amount of process energy used per ton of product (measured in British thermal units or Btu), and the fuel 
mix (e.g., diesel oil, natural gas, fuel oil). Next, emissions factors for each type of fuel were used to 
convert fuel consumption to GHG emissions. As noted earlier, making a material from recycled inputs 
generally requires less process energy (and uses a different fuel mix) than making the material from virgin 
inputs. 

The fuel mixes used in these calculations reflect the average U.S. fuel mixes for each 
manufacturing process. However, it is worth noting that U.S. consumer products (which eventually 
become MSW) increasingly come from overseas, where the fuel mixes may be different. For example, 
China relies heavily on coal and generally uses energy less efficiently than the United States. 
Consequently the GHG emissions associated with the manufacture of a material in China may be higher 
than for the same material made in this country. In addition, greater energy is likely to be expended on 
transportation to China than on transportation associated with domestic recycling. However, such 
analysis is beyond the scope of this report, which focuses only on domestic production, transportation, 
consumption, and disposal. 

Details of the methodology for estimating process energy GHG emissions are provided in 
Chapter 2. 

Transportation Energy GHG Emissions : Transportation energy GHG emissions consist of C0 2 
emissions from the combustion of fuels used to transport raw materials and intermediate products to the 
retail/distribution point. The estimates of transportation energy emissions for transportation of raw 
materials to the manufacturing or fabrication facility are based on: (1) the amounts of raw material inputs 
and intermediate products used in manufacturing 1 ton of each material; (2) the average distance that each 
raw material input or intermediate product is transported; and (3) the transportation modes and fuels used. 
For the amounts of fuel used, the study used data on the average fuel consumption per ton-mile for each 
mode of transportation (this information can be found in Background Document A 24 ). Then an emission 
factor for each type of fuel was used to convert the amount of each type of fuel consumed to the GHG 
emissions produced. 

This edition includes estimates of GHG emissions from transporting manufactured products or 
materials from the manufacturing point to the retail/distribution point. The U.S. Census Bureau along 
with the Bureau of Transportation Statistics recently conducted a Commodity Flow Survey that 
determined the average distance commodities were shipped in the United States and the percentage each 
of the various transportation modes was used to ship these commodities. 2 '' However, there is large 
variability in the shipping distance and modes used, and so transportation emission estimates given here 
are somewhat uncertain. More detail on the methodology used to estimate transportation energy GHG 
emissions is provided in Chapter 2. 

Process Nonenergy GHG Emissions : Some GHG emissions occur during the manufacture of 
certain materials and are not associated with energy consumption. In this analysis, these emissions are 
referred to as process nonenergy emissions. For example, the production of steel or aluminum requires 
lime (calcium oxide, or CaO), which is produced from limestone (calcium carbonate, or CaC0 3 ), and the 
manufacture of lime results in C0 2 emissions. Other process nonenergy GHG emissions are associated 


24 Background Document A: A Life Cycle of Process and Transportation Energy’for Eight Different Materials. 
Available at EPA’s Global Wanning—Waste, “Background Documents for Solid Waste Management and GHG 
Report” website. Op cit. 

25 U.S. Census Bureau, 2003. Commodity / Flow Survey. United States Census Bureau. December, 2003. Available 
online at: http:// www.census.gov/prod/ec02/02tcf-usp.pdf . 


11 






with the manufacture of plastics, office paper, and medium-density tiberboard. In some cases, process 
nonenergy GHG emissions are associated only with production using virgin inputs; in other cases, these 
emissions result when either virgin or recycled inputs are used. These emissions are described in Chapter 
2. 

Carbon Sinks : The only carbon sink associated with the raw materials acquisition and 
manufacturing stage is the additional carbon sequestration in trees associated with source reduction or 
recycling of paper products. The methodology for estimating forest carbon sequestration is described in 
Chapter 3. 

1.4.2 GHG Emissions and Carbon Sinks Associated with Waste Management 

As shown in Exhibit 1-3, there are up to five postconsumer waste management options, 
depending on the material: source reduction, recycling, composting, combustion, and landfilling. This 
section describes the GHG emissions and carbon sinks associated with each option. 

Source Reduction : In this analysis, source reduction is measured by the amount of material that 
would otherwise be produced but is not generated due to a program promoting source reduction. The 
avoided GHG emissions are based on raw material acquisition and manufacturing processes for the 
average current mix of virgin and recycled inputs for materials in the marketplace. * 2 ' 1 There are no 
emissions from MSW management. 

Recycling : When a material is recycled, it is used in place of virgin inputs in the manufacturing 
process. The avoided GHG emissions from remanufacture using recycled inputs is calculated as the 
difference between (1) the GHG emissions from manufacturing a material from 100 percent recycled 
inputs, and (2) the GHG emissions from manufacturing an equivalent amount of the material (accounting 
for loss rates) from 100 percent virgin inputs (including the process of collecting and transporting the 
recyclables). No GHG emissions occur at the MSW management stage because the recycled material is 
diverted from waste management facilities. 27 (If the product made from the recycled material is later 
composted, combusted, or landfilled, the GHG emissions at that point would be attributed to the product 
that was made from the recycled material.) Chapter 3 details GHG emissions from recycling. 

Materials are recycled either in “closed-loop” or “open-loop” processes. Closed loop means that 
a product is recycled into the same product; an example is an aluminum can recycled into another 
aluminum can. Open loop means that the secondary product is different than the primary product and 
often occurs when a material is degraded or changed by the recycling process. Most of the materials 
considered in this analysis are modeled as being recycled in a closed loop. However, a variety of paper 
types are recycled under the general heading of “mixed paper.” Mixed paper can be remanufactured, via 
an open loop, into boxboard or paper towels. Other materials are recycled in open-loop processes, but 
due to limited resources, this study could not analyze all open-loop processes. 28 Three newly added 
materials, fly ash, carpet, and PCs, are analyzed only in an open-loop process. In the case of PCs, the 
used computers are sent to a processing facility where various components, such as copper, lead, glass, 
and plastic, are put into separate streams. Carpet is also remanufactured into secondary materials other 
than carpet. 


26 Changes in the mix of production (i.e., higher proportions of either virgin or recycled inputs) result in incremental 
emissions (or reductions) with respect to this reference point. 

2 The EPA researchers did not include GHG emissions from managing residues (e.g., wastewater treatment 
sludges) from the manufacturing process for either virgin or recycled inputs. 

28 For example, not all steel cans are recycled into more steel cans; not all aluminum cans are recycled into more 
aluminum cans, but for the purposes of this report, EPA assumes they are. 


12 






C0 2 Emissions from Biogenic Sources 

The United States and all other parties to the UNFCCC agreed to develop inventories of GHG emissions 
as part of its stated goals of stabilizing emissions and preventing dangerous anthropogenic climate change. The 
IPCC developed a set of inventory methods to be used as the international standard. (IPCC 1997. IPCC 
Guidelines for National Greenhouse Gas Inventories, three volumes.) The methodologies used in this report to 
evaluate emissions and sinks of GHGs are consistent with the IPCC guidance. 

One of the elements of the IPCC guidance that deserves special mention is the approach used to address 
C0 2 emissions from biogenic sources. For many countries, the treatment of C0 2 releases from biogenic sources 
is most important when addressing releases from energy derived from biomass (e.g., burning wood), but this 
element is also important when evaluating waste management emissions (for example, the decomposition or 
combustion of grass clippings or paper). The carbon in paper and grass trimmings was originally removed from 
the atmosphere by photosynthesis, and under natural conditions, it would cycle back to the atmosphere 
eventually as C0 2 due to degradation processes. The quantity of carbon that these natural processes cycle 
through the Earth's atmosphere, waters, soils, and biota is much greater than the quantity added by 
anthropogenic GHG sources. But the focus of the UNFCCC is on anthropogenic emissions—those resulting from 
human activities and subject to human control. Those emissions have the potential to alter the climate by 
disrupting the natural balances in carbon's biogeochemical cycle and altering the atmosphere’s heat-trapping 
ability. For processes with C0 2 emissions, if the emissions are from biogenic materials and the materials are 
grown on a sustainable basis, then those emissions are considered simply to close the loop in the natural carbon 
cycle. They return to the atmosphere C0 2 that was originally removed by photosynthesis. In this case, the C0 2 
emissions are the C0 2 emissions are not anthropogenic and therefore not included in emission inventories. (For 
purposes of this analysis, biogenic materials are paper, yard trimmings, and food discards.) On the other hand. 
C0 2 emissions from burning fossil fuels are counted because these emissions would not enter the cycle were it 
not for human activity. Likewise, CH 4 emissions from landfills are counted. Even though the source of carbon 
is primarily biogenic, CH 4 would not be emitted were it not for the human activity of landfilling the waste, which 
creates anaerobic conditions conducive to CH 4 formation. Note that this approach does not distinguish between 
the timing of C0 2 emissions, provided that they occur in a reasonably short time scale relative to the speed of the 
processes that affect global climate change. In other words, as long as the biogenic carbon would eventually be 
released as C0 2 , whether it is released virtually instantaneously (e.g., from combustion) or over a period of a few 
decades (e.g., decomposition on the forest floor), it is treated the same. 


Composting : When organic materials are composted, the anaerobic decomposition of materials 
produces CH 4 . Similarly, the collection and transportation of organics produces nonbiogenic emissions. 
During the composting process and after the compost is added to the soil, the decomposition of plants 
produces biogenic C0 2 emissions. All of the materials that may be composted (e.g., leaves, brush, grass, 
food waste, newspaper) originally are produced by trees or other plants. As described in the above “C0 2 
Emissions from Biogenic Sources,” the biogenic CO : emitted from these materials during composting is 
not counted toward GHG emissions. However, composting does result in increased soil carbon storage 
due to increased production of humic material (natural organic polymers, which degrade at a slow rate) 
and several other factors, which are described in Chapter 4. 

Although composting may result in some production of CH 4 (due to anaerobic decomposition in 
the center of the compost pile), compost researchers believe that the CH 4 almost always oxidizes to C0 2 
before it escapes from the compost pile. 

Because the C0 2 emissions from composting are biogenic, and well-managed compost piles are 
not believed to produce CH 4 , the only GHG emissions from composting result from transportation of 
compostable materials to composting facilities and mechanical turning ot the compost piles. GHG 
emissions associated with compost application are discussed in Chapter 4. 


13 




Combustion : When waste is combusted, two GHGs are emitted: C0 2 and N 2 0. Nonbiogenic C0 2 
emitted during combustion (i.e., C0 2 from plastics) is counted toward the GHG emissions associated with 
combustion, but biogenic C0 2 is not. Because most waste combustors produce electricity that substitutes 
for utility-generated electricity, the net GHG emissions are calculated by subtracting the utility GHG 
emissions avoided from the gross GHG emissions. GHG emissions from combustion are described in 
Chapter 5. 

Landfilling : When organic matter is landfilled, some of this matter decomposes anaerobically and 
releases CH 4 , a GHG. Some of the organic matter never decomposes at all; instead, the carbon becomes 
stored in the landfill. (Landfilling of metals and plastics does not result in CH 4 emissions or carbon 
storage.) 

At some landfills, virtually all of the CH 4 produced is released to the atmosphere. At others, CH 4 
is captured for flaring or combustion with energy recovery (e.g., electricity production). Almost all of the 
captured CH 4 is converted to CO?, but that C0 2 is not counted in this study as a GHG because it is 
biogenic. With combustion of CH 4 for energy recovery, emission factors reflect the electric utility GHG 
emissions avoided. Regardless of the fate of the CH 4 , the landfill carbon storage associated with 
landfilling of some organic materials is accounted for. GHG emissions and carbon sinks from landfilling 
are described in Chapter 6. 

1.5 ESTIMATING AND COMPARING NET GHG EMISSIONS 

To calculate the net GHG implications of a waste management strategy for a given material, 
baseline and alternative scenarios must be established. For example, a baseline scenario in which 10 tons 
of office paper are manufactured, used, and landfilled could be compared with an alternative scenario in 
which 10 tons are manufactured, used, and recycled. For this example, net GHG emissions are calculated 
as the difference between landfilling emissions and the emissions/emission reductions associated with 
recycling. The general formula for net GHG emissions for each scenario is as follows: 

Net GHG emissions = Gross manufacturing GHG emissions - (Increase in carbon stocks + 
Avoided utility GHG emissions) 

Comparing net GHG emissions for the two scenarios enables the lowest net GHG emissions to be 
identified. The following circumstances influence the net GHG emissions of a material: 

• Through source reduction (for example, “lightweighting” a beverage can—using less aluminum 
for the same function), GHG emissions throughout the life cycle are avoided. In addition, when 
paper products are source reduced, additional carbon is sequestered in forests, through reduced 
tree harvesting. 

• Through recycling , the GHG emissions from making an equivalent amount of material from 
virgin inputs are avoided. In most cases, recycling reduces GHG emissions because 
manufacturing a product from recycled inputs requires less energy than making the product from 
virgin inputs. 

• Composting results in carbon sequestration of organic materials. 

• Landfilling results in CH 4 emissions. If captured, the CH 4 may be flared, which simply reduces 
CH 4 emissions (since the C0 2 produced by flaring is biogenic in origin, it is not accounted for in 
this assessment of anthropogenic emissions). If captured CH 4 is burned to produce energy, it 
offsets emissions from fossil fuel consumption. 

• Combustion of waste may result in an emissions offset if the waste is burned in a waste-to-energy 
facility, which displaces fossil-fuel derived electricity. 


14 




In calculating emissions for the life-cycle scenarios, one can utilize a “raw material extraction” 
reference point, or a “waste generation” reference point. The raw material extraction reference point is a 
cradle-to-grave approach, in which emissions are calculated starting with the extraction of raw materials 
(e.g., ore) used to create virgin inputs. Since this report is designed to be used mainly by solid waste 
managers, the emission factors presented in the main body of the document are based on the waste 
generation reference point, one that starts when a material is discarded. Emission factors using a raw 
material extraction reference point are presented in the Appendices. 

Exhibit 1-3 indicates how GHG sources and sinks have been counted for each MSW management 
strategy in order to estimate net GHG emissions using the postconsumer waste generation reference point. 
For example, the top row of the exhibit shows that source reduction (1) reduces GHG emissions from raw 
materials acquisition and manufacturing, (2) results in an increase in forest carbon sequestration, and (3) 
does not result in GHG emissions from waste management. The sum of emissions (and sinks) across all 
steps in the life cycle represents net emissions. Section 7.2, “Accounting for Emission Reductions and 
Energy Savings,” describes how waste managers and companies have used these emission factors to 
estimate GHG emissions and potential GHG emission reductions associated with integrated waste 
management. In addition, EPA uses these emission factors to develop WARM, which enables users to 
analyze the GHG savings associated with changing their waste management practices. EPA also recently 
developed the ReCon Tool and the Durable Goods Calculator (DGC). The ReCon tool helps both 
individual and corporate consumers calculate the GHG and energy benefits of purchasing or 
manufacturing materials with varying recycled content; the DGC allows consumers to calculate the GHG 
and energy impacts of different disposal methods for durable goods such as refrigerators and televisions. 
As with WARM, the ReCon Tool is available as both an online calculator and as a spreadsheet tool, while 
the DGC is currently available only as a spreadsheet tool. 29 


29 Available at the EPA, Global Wanning—Waste website. Op cit. WARM and ReCon are available at: 
http://www.epa.gov/mswclimate , then follow link to Tools. 


15 




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16 


2. RAW MATERIALS ACQUISITION AND MANUFACTURING 


The GHG emissions associated with raw materials acquisition and manufacturing are a key 
element of a life-cycle GHG analysis. This chapter describes how EPA estimated these emissions for 21 
materials: aluminum cans, steel cans, copper wire, glass, three types of plastic (HDPE, LDPE, and PET), 
corrugated cardboard, magazines/third-class mail, newspaper, office paper, phonebooks, textbooks, 
dimensional lumber, medium-density fiberboard, carpet, personal computers, clay bricks, concrete, fly 
ash, and tires. This chapter also includes a similar analysis for three definitions of mixed paper (broad, 
residential, and office). 

In manufacturing, substantial amounts of energy are used both in the acquisition of raw materials 
and in the manufacturing process itself. In general, the majority of energy used for these activities is 
derived from fossil fuels. Combustion of fossil fuels results in emissions of C0 2 , a GHG. In addition, 
manufacturing of some materials also results in GHG emissions that are not associated with energy 
consumption. Section 2.1 addresses energy-related C0 2 emissions, and Section 2.2 covers nonenergy 
GHG emissions. Sections 2.3 and 2.4 discuss results and limitations of the analysis, respectively. 

2.1 GHG EMISSIONS FROM ENERGY USE IN RAW MATERIALS ACQUISITION AND 
MANUFACTURING 

To begin this analysis, EPA estimated the GHG emissions from fossil fuel combustion for both 
(1) raw materials acquisition and manufacturing (referred to here as “process energy”), and (2) 
transportation (referred to as “transportation energy”). 

In this analysis, process energy GHG emissions consist primarily of C0 2 . 1 The majority of C0 2 
emissions are from combustion of fuels used directly, e.g., to operate mining equipment or fuel a blast 
furnace. C0 2 emissions from fuels used to generate electricity during the manufacturing stage also are 
included in process energy emissions. In addition, process energy GHG emissions include indirect 
emissions from “precombustion” activities, such as oil exploration and extraction, coal mining and 
beneficiation, and natural gas production. 

Transportation energy GHG emissions consist of C0 2 emissions from combustion of fuels used to 
transport raw materials and intermediate products to the final manufacturing or fabrication facility. For 
transportation of recycled inputs, this analysis considers transportation (1) from the curbside to the 
materials recovery facility (MRF), (2) from the MRF to a broker, and (3) from a broker to the plant or 
mill where the recycled inputs are used. The transportation values for recycled inputs generally include 
the energy used to process the inputs at a MRF. Transportation of finished manufactured goods to 
consumers is not included in the analysis; however, this edition of the report does include transportation 
emissions from the manufacturer to the retailer. EPA did not estimate transportation emissions of CH 4 or 
N 2 0; these emissions are considerably less significant than C0 2 emissions from transportation activities. 2 
This omission would tend to understate the GHG impacts from transportation slightly. 

Emissions from raw materials acquisition and manufacturing also include CH 4 associated with 
producing, processing, and transporting coal, oil, and natural gas. CH 4 is emitted during the various 
stages of fossil fuel production because CH 4 is trapped within coal and oil deposits, and is released when 
they are mined. Natural gas, of course, consists largely of CEE. 


1 Note, however, that C0 2 emissions from combustion of biomass (e.g., in paper manufacturing) are not counted as 
GHG emissions (as described in Chapter 1). 

2 The Inventory ofU.S. Greenhouse Gas Emissions and Sinks: 1990-2004 estimates 2004 emissions from 
transportation to be 506.0 MMTCE for C0 2 and 12.1 MMTCE tor CH 4 and N 2 0 combined. 


17 





EPA developed separate estimates for GHG emissions from process and transportation energy for 
virgin inputs and recycled inputs, generating a total of four separate GHG emission estimates for each 
material: (1) process energy with virgin inputs, (2) process energy with recycled inputs, (3) transportation 
energy for materials made from virgin inputs, and (4) transportation energy for materials made trom 
recycled inputs. 

2.1.1 Methodology 

Virgin and recycled emission estimates for material processing and transportation were developed 
using two sets of data: (1) the amount of each type of fuel consumed per ton of the material, and (2) the 
“carbon coefficient” for each fuel (a factor that translates the energy value of fuel combusted into the 
mass of GHGs emitted). 

EPA’s methodology in using these two sets of data to estimate process and transportation energy 
GHG emissions is best illustrated by an example. To estimate process energy GHG emissions from the 
production of 1 ton of steel from virgin inputs, the EPA researchers multiplied the amount of each type of 
fuel consumed (as measured in million Btu) by the carbon coefficient for that type of fuel (as measured in 
metric tons of carbon equivalent, or MTCE, per million Btu). The result was an estimate of the GHG 
emissions (in MTCE) from the combustion of each type of fuel required to make 1 ton of steel. Total 
process energy GHG emissions from making 1 ton of steel are simply the sum of the GHG emissions 
across all of the fuel types. To estimate the GHG emissions when electricity is used, EPA used the 
national average mix of fuels used to generate electricity. 

EPA estimated GHGs from the energy used to transport raw materials necessary for 1 ton of a 
given product (e.g., steel) to the retailer, and the energy used to transport the product from the 
manufacturer to the retail point, in the same way. The amount of each fuel used was multiplied by its 
carbon coefficient, and the resulting values for each of the fuels were summed to yield total transportation 
energy GHG emissions. 

In this way, GHG estimates for raw materials acquisition and manufacturing were developed for 
each of the manufactured materials considered. As noted in Chapter 1, much of the energy information 
reflected in the analysis is drawn from an effort conducted by EPA’s ORD to construct a Decision 
Support Tool for solid waste managers. The remaining energy data were developed by FAL as part of the 
original effort or subsequent updates. 

Most of the materials included in this analysis are assumed to undergo closed-loop recycling (i.e., 
primary material type is remanufactured into the same material type). However, several materials are 
recycled in an open loop, where the primary material type is remanufactured into a different secondary 
material; these materials are mixed paper, corrugated cardboard, fly ash, carpet, and personal computers. 
The exhibits in this chapter show data not only for the 21 primary materials of interest, but also for 
secondary materials such as boxboard, carpet pad, carpet backing, molded auto parts, asphalt, CRT glass, 
lead bullion, and copper wire. Because recycling processes data are similar for HDPE, LDPE, and PET, 
EPA adopted the approach used by ORD of using a single energy profile (fuel mix and energy intensity) 
for all recycled plastics. For steel cans, EPA developed the GHG estimates for virgin production using 
the basic oxygen furnace process, and for recycled production, electric arc furnace process was used. 3 


3 Two types of furnace are used in recycling steel: electric arc (EAF), which uses nearly 100 percent recovered 
inputs, and basic oxygen (BOF), which uses 25 to 35 percent recovered steel. Steel from EAFs is structurally 
unsuited to milling into thin sheets to make steel cans. Therefore, although EPA models steel can recycling as a 
closed-loop process (steel cans made into steel cans), this is not entirely accurate, statistically. By modeling 
recovery of steel cans as a closed-loop process, EPA implicitly assumed that 1 ton of steel produced from recovered 
steel cans in an electric arc furnace displaces 1 ton of steel produced from virgin inputs in a basic oxygen furnace. 
However, the EPA researchers feel that the values from the two furnaces are close enough to make closed-loop 


18 



Carbon coefficients from DOE’s Energy Information Administration for all energy sources 
except electricity were used. * * 4 The carbon coefficient for electricity was based on the weighted average 
carbon coefficients for all fuels used to generate electricity in the United States. 5 

Because the carbon coefficients from these sources only account for the C0 2 emissions from 
combustion of each type of fuel, EPA added to these carbon coefficients (1) the average amount of CH4 
emitted during the production, processing, and transportation of fossil fuels, and (2) the average C0 2 
emissions from oil production, due to the flaring of natural gas. EPA calculated the average fugitive 
GHG emissions associated with U.S. production of coal, oil, and natural gas. The resulting average 
estimates for fugitive GHG emissions from fossil fuel production were 0.92 kg of carbon equivalent per 
million Btu (kg CE/million Btu) for coal, 0.10 kg CE/million Btu for oil, and 0.70 kg CE/million Btu for 
natural gas. 6 

The carbon coefficients that reflect both C0 2 and CH 4 emissions are supplied in Exhibit 2-1. (All 
exhibits are provided at the end of this chapter.) 

The fuel mixes used in these calculations reflect the average U.S. fuel mixes for each process. 
However, it is worth noting that U.S. consumer products (which eventually become MSW) increasingly 
come from overseas, where the fuel mixes may be different. For example, China relies heavily on coal 
and generally uses energy less efficiently than the United States. Consequently the GHG emissions 
associated with the manufacture of a given product in China may be higher than for the same product 
made in this country. However, such analysis is beyond the scope of this report, which focuses only on 
domestic production, transportation, consumption, and disposal. 

The process and transportation GHG values are summarized in Exhibit 2-2. For each product and 
each type of input (virgin or recycled), EPA summed the estimates for process and transportation GHG 
emissions, as shown in columns “b” (for virgin inputs) and “c” (for recycled inputs) of Exhibit 2-2. EPA 
also estimated the energy-related GHG emissions from manufacturing each material from the current mix 
of virgin and recycled inputs. 7 These values are shown in column “e.” (The remaining two columns of 
Exhibit 2-2 are discussed later in this chapter.) 

The energy intensity and fuel mix data are provided in Exhibit 2-3 through Exhibit 2-6. For most 
materials, the data in the exhibits are for manufacturing processes that either use (1) 100 percent virgin 
inputs or (2) 100 percent recycled inputs. 8 

To estimate the types and amounts of fuels used for process and transportation energy, ORD and 
FAL relied on published data (such as engineering handbooks and published production data), contacts 


recycling a reasonable assumption. (For the fabrication energy required to make steel cans from steel, EPA used the 

values for fabrication of steel cans from steel produced in a basic oxygen furnace.) 

4 DOE, Energy Information Administration. 2004. Annual Energy Review: 2003. 

5 FAL reported the Btu value for electricity in terms of the Btu of fuel combusted to generate the electricity used at 
the factory, rather than the (much lower) Btu value of the electricity that is delivered to the manufacturer. Thus, 
FAL had already accounted for the efficiency of converting fuels to electricity, and the losses in transmission and 
distribution of electricity. EPA therefore did not need to account for these factors in the carbon coefficient for 
electricity. 

6 ICF Consulting. 1995. Memorandum, “Fugitive Methane Emissions from Production of Coal, Natural Gas, and 
Oil,” August 8, updated to use global warming potential for CH 4 of 21. 

7 The current mix of virgin and recycled inputs is derived from FAL data, and varies from material to material. 

8 In the FAL data set, the one exception is the data for steel cans made from virgin inputs, for which FAL provided 
data for manufacture from 80 percent virgin inputs and 20 percent recycled inputs. EPA (or ICF Consulting) 
extrapolated from this data (and the corresponding values for production using 100 percent recycled inputs) to 
obtain estimates of the energy inputs for manufacturing these materials from 100 percent virgin inputs. Similarly, 
for corrugated cardboard, ORD assumed that a virgin corrugated box contains a minimum of 14.7 percent total 
recycled content. 


19 



with industry experts, and review by stakeholders and trade organizations. ORD and FAL counted all 
energy, no matter where it was used. For example, much aluminum produced in the United States is 
made from bauxite that is mined and processed into alumina in other countries. The energy required for 
overseas bauxite mining and processing is included in the analysis. 

The EPA methodology also accounts for GHG emissions associated with the transport of 
materials as commodities (i.e., manufactured products or materials) from the manufacturing point to the 
retail/distribution point. The U.S. Census Bureau along with the Bureau of Transportation Statistics 
recently conducted a Commodity Flow Survey that determined the average distance commodities were 
shipped in the United States and the percentage each of the various transportation modes was used in 
shipping these commodities. 9 The estimated transportation energy for each material type was estimated 
by applying the transportation fuel efficiency and fuel-specific heating value to the average miles that 
commodities were shipped within each mode. Although these factors may be small relative to the larger 
raw materials acquisition and manufacturing emissions for each material, their inclusion adds to the 
robustness of the life-cycle methodology. Because this adjustment was made to both the 100 percent 
virgin and 100 percent recycled material types, the change in transportation emissions will drop out when 
virgin and recycled materials are compared. Because source reduction emission factors reflect the benefit 
of not transporting the material in the first place, the adjustment will be more noticeable. For additional 
details on the methodology for estimating retail transportation for materials please see the WARM Retail 
Transportation background document. 10 

Finally, it should be noted that during EPA’s extensive review of ORD and FAL data, the most 
critical assumptions and data elements that each model used were examined to ensure that they accurately 
reflect the energy requirements of the raw materials acquisition and manufacturing for the material types 
considered. Nevertheless, EPA recognizes that different manufacturers making the same product use 
somewhat different processes with different energy requirements and fuel mixes, and that there are 
limited data on the extent to which various processes are used. Thus, although the goal was to estimate as 
accurately as possible the national average GHG emissions for the manufacture of each material from 
virgin and recycled inputs, individual manufacturers will likely have GHG emissions that vary 
significantly from those estimated here. 

2.2 NONENERGY GHG EMISSIONS FROM MANUFACTURING AND RAW MATERIALS 
ACQUISITION 

In addition to GHG emissions from energy use, EPA researchers accounted for three additional 
sources of GHGs in manufacturing processes: 

• When limestone (CaC0 3 ) is converted to lime (CaO), C0 2 is emitted. Significant quantities of 
lime are used in the production of cement,” steel, aluminum, and, to a much lesser extent, office 
paper. 

• CH 4 emissions from natural gas pipelines and processing of natural gas are associated with the 
manufacture of plastic products. 

• PFCs (CF 4 and C 2 F 6 ) are emitted during aluminum smelting. 


9 U.S. Census Bureau, 2003. Commodity Flow Survey. United States Census Bureau. December 2003. Available 
online at: www.census.gov/prod/ec02/02tcf-usp.pdf 

10 Available at EPA’s Global Wanning—Waste, “Background Documents for Solid Waste Management and GHG 
Report” website: http://www.epa.gov/mswclimate. then follow links to Publications -> Reports, Papers, and 
Presentations -> This report -> Background Documents. 

11 For the category “concrete” the material being replaced is not the cement, but rather the aggregate (i.e. sand and 
rock) portion of concrete. However fly ash is used as a cement replacement in concrete, and the nonenergy 
emissions of the replaced virgin cement are accounted for in estimations for the “fly ash” category. 


20 





The process nonenergy GHGs for each material are shown in the second-to-last column of 
Exhibit 2-3 and Exhibit 2-5 (for manufacture from virgin inputs and recycled inputs, respectively), and 
are repeated in column “f' of Exhibit 2-2. ORD supplied the nonenergy C0 2 emissions for glass, 
corrugated cardboard, and newspaper. EPA based the calculation for PFC and C0 2 emissions from 
aluminum on the Inventory ofU.S. Greenhouse Gas Emissions and Sinks: 1990-2004 . 12 

Nonenergy C0 2 emissions for the other materials, as well as CH 4 emissions, are based on the 
original analysis supporting the first edition of this report. 13 

2.3 RESULTS 

The estimates of the total GHG emissions from raw materials acquisition and manufacturing for 
each material are shown in Exhibit 2-2, column “g.” In order to obtain these estimates, EPA summed the 
energy-related GHG emissions (column “e”) and the nonenergy GHG emissions (column “f’). The 
estimates in column “g” correspond to the type of inputs that occur during the recycling process: virgin 
inputs, recycled inputs, or the current mix of virgin and recycled inputs. 

The process energy and transportation GHG values for virgin and recycled production are shown 
in the third-to-last columns of Exhibit 2-3 and Exhibit 2-5, and in the last columns of Exhibit 2-4 and 
Exhibit 2-6 (the last columns of Exhibit 2-3 and Exhibit 2-5 show the total process energy GHG 
emissions). The retail transport energy and emission values are presented in Exhibit 2-7. 

2.4 LIMITATIONS 

There are several limitations to the analysis of the GHG emissions associated with raw materials 
acquisition and manufacturing, as described below. 

The approach used in this analysis provides values for the average GHG emission rates per ton of 
material produced, not the marginal emission rates per incremental ton produced. In some cases, the 
marginal emission rates may be significantly different. For example, reducing the production of plastic 
products from virgin inputs may not result in a proportional decrease in CH 4 emissions from natural gas 
pipelines and natural gas processing. The operating pressure in natural gas pipelines and the number and 
size of leaks in the pipeline determine CH 4 emissions from natural gas pipelines. Consequently, the 
amount of natural gas consumed at one end of the pipeline (e.g., to make plastic) does not affect the level 
of pipeline CH 4 emissions in a direct, linear way. As another example, long-term reductions in electricity 
demand could selectively reduce demand for specific fuels, rather than reducing demand for all fuels in 
proportion to their representation in the current average fuel mix. This analysis estimates average carbon 
conversion rates largely because the marginal rates are much more difficult to estimate. Nevertheless, 
EPA believes the average values provide a reasonable approximation of the GHG emissions. 

In addition, the analysis assumes that the GHG emissions from manufacturing a given product 
change in a linear fashion as the percentage of recycled inputs moves from 0 to 100 percent. In other 
words, the analysis assumes that both the energy intensity and the fuel mix change in linear paths over 
this range. However, it could be that GHG emissions from manufacturing move in a nonlinear path, (e.g., 
some form of step function) when the percentage of recycled inputs changes, due to capacity limits in 
manufacturing or due to the economics of manufacturing processes. 


12 To estimate aluminum PFC emissions on a per-ton basis, EPA divided the inventory estimates for CF 4 and C 2 F 6 
emissions from aluminum by total primary aluminum production, yielding units in MTCE/ton. 

13 ICF Consulting. 1994. Memorandum, “Detailed Analysis of Greenhouse Gas Emissions Reductions from 
Increased Recycling and Source Reduction of Municipal Solid Waste,” July 29, p. 48 of the Appendix prepared by 
FAL, dated July 14, 1994. 


21 



The information used in this analysis represents the best available data from published and 
unpublished industry sources, some of it quite dated. Therefore, the data may not necessarily reflect 
recent trends in industrial energy efficiency or changes in the fuel mix. 

Finally, this static analysis does not consider potential future changes in energy usage per unit of 
output or alternative energy (e.g., nonfossil) sources. Reductions in energy inputs due to efficiency 
improvements could occur in either virgin input processes or recycled input processes. Efficiency 
improvements and switching to alternative energy sources will result directly in GHG emissions 
reductions and may change the reductions possible through increased recycling or source reduction. 


22 


Exhibit 2-1 

Carbon Coefficients For Selected Fuels (Per Million Btu) 


Fuel Type 

Metric Tons 
of C0 2 from 
Combustion 

kg Carbon 
Equivalent 
(CE) from 
Combustion 

Metric 
Tons of 
Fugitive 

ch 4 

Emissions 

kg CE from 
Fugitive 
Methane 
Emissions 

kg CE 
Emitted 

Gasoline 

0.07 

19.05 

0.00002 

0.10 

19.15 

LPG 

0.06 

16.81 

0.00002 

0.10 

16.91 

Distillate Fuel 

0.07 

19.65 

0.00002 

0.10 

19.75 

Residual Fuel 

0.08 

21.18 

0.00002 

0.10 

21.28 

Diesel 

0.07 

19.65 

0.00002 

0.10 

19.75 

Oil/Lubricants 

0.07 

19.94 

0.00002 

0.10 

20.04 

Steam (nonpaper products) 

0.07 

18.07 

0.00011 

0.61 

18.81 

Steam (paper products) 

0.05 

12.80 

0.00004 

0.25 

13.17 

National Average Fuel Mix for 
Electricity 

0.06 

15.26 

0.00010 

0.57 

15.83 

National Average Fossil Fuel 
Mix for Electricity 

0.08 

22.17 

0.00015 

0.83 

23.01 

Coal Used for Electricity 

0.09 

24.80 

0.00016 

0.92 

25.72 

Coal Used by Industry 
(Noncoking Coal) 

0.09 

25.10 

0.00016 

0.92 

26.02 

Petroleum Coke 

0.10 

27.57 

- 

- 

27.57 

Metallurgical Coke 

0.11 

30.69 

- 

- 

30.69 

Natural Gas 

0.05 

13.62 

0.00012 

0.70 

14.33 

Nuclear 

0.00 

0.84 

- 

- 

0.84 

Wastes 

0.07 

19.42 

0.00000 

0.01 

19.61 


23 










Exhibit 2-2 

GHG Emissions from the Manufacture of Selected Materials 
_ (MTCE per Ton of Product) 


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_0> 

LU 


^ o cm in o 

co o o i— o 

d d d o 

CM 


o 

o 


o 

o 


ooo-’-cDr'-h-ooooT-o-o-T-o 

OOOOI^t^CMCMOOOincOOOO 

dddoT-T^T^ddddcMCModd 


CM 

dT 


LO 

in 

T- 

1^ 

O 

o 

CO 

CD 

03 

03 

CO 


o 

o 

o 

O) 

CD 

o 

m 

CO 

00 

CM 

o 

CM 

03 

m 

03 

O 

T“ 

03 


00 

in 


CD 

o 

o 

o 

T- 

CM 

CO 

CO 

03 

o 

00 

r^' 

c\i 

00 

00 


o 

00 

03 

03 

X— 

T- 


o 

o 

d 

d 

in 

r-2 

CD 

CD 



03 

CD 

h- 

00 

03 

CO 

o 

03 

03 

03 

in 

in 


CO 

o 

o 

o 

co 


1^ 

oo 

co 


M 

c n o 
ra 

.2 i 

CQ 


in o cd oo¬ 
ooo o o 
d d d d d 


o 

d 


in 

o 


ooooininininoooininininin 

oqqqqqqqqqqqqqqq 

dodddddddddddddd 


co 

CD 

CD 

O 

dT 

t'- 

CO 

o 

CD 

in 

CM 

T— 

o 

in 

CM 

o 

o 

o 

in 

oo 

CO 

o 

in 

CM 

r-*- 

T— 

O 

CD 

CM 

CD 

o 

O 

o 

in 

CD 

CD 

r- 

CM 

o 

o 

o 

T— 

03 



oo 

o 



d 

CM 

o 

CO 

o 

o 

d 

o 

oo 

o 

CO 

o 

d 

o 

d 

CO 

r— 

CO 

in 

CO 

00 










CM 

CO 

CN 

CD 






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<13 

a: 


in 

o 

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LL 

CD 

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co 

b 


03 

CO 


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03 

co 


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03 

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ooqq-o-qq-ooqqq-oqo;-^ 

dddddddddddddddo 


0 

0. 


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o 

00 

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00 

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00 

co 

00 

o 

o 

o 

o 

o 

o 

o 

o 

o 

o 

o 

o 

o 

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o 

o 

o 

o 

o 

o 

o 

o 

o 

o 

d 

d 

o 

o 

o 

d 

o 

o 

d 

o 

o 

d 

o 

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d 

o 

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d 

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t— qoqq^ZZ^Z^ZZZ 0 ^ 
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T- O T- CO CD < 

in CM O’ CD CM 2 

t- 1 d d d d 


u 

3 

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a. 

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03 

a 

>< 


w 

c 

re 

O 

E 

3 

C 

E 

3 


CO 

c 

re 

O 

0 

03 


re 

o 

V_ 

03 

i 

c 

L_ 

1_ 

re 

re 

CL 

CL 

CL 

CL 

o 

O 


re 

o 

-O 

■O 

L_ 

re 

O 


CO 

CO 

re 

o 

■ 

"O 


03 


03 

XI 

E 

3 


re 


re 

o 

XI 

i_ 

03 

X 


1/3 

C 


< CO 






TO 

CD 

-*—> 

CO 

re 

re 

CL 

CL 

re 

O 

o 

(/) 

c 

o 

LU 

“O 

1 

T3 

L_ 





03 

c 

re 

Q. 

-Q 

O 

'0 

E 

03 





O) 

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Q. 


0 

o 

c 

3 

o 

c n 

LU 

LU 


ZJ 

re 

C/3 

re 

c 

_Q 

0 


_Q 

c/) 

Q. 

0 . 

\— 

1 _ 

L_ 

03 

5 

o 

o 

■ 4 — > 

X 

F 

TO 

X 

03 

O 

Q 

LU 

o 

re 

re 

E 

x: 

0 


0 

o 

rn 

T 

i 

n 



z 

o 

Q_ 

1 — 

b 

2 

CO 


w 

03 

5 

o 

I— 


03 

Q. 


03 

c 

d 

•o 

re 

0. 

re 

CL 


03 

c 

o 

re 

CQ 

re 

CL 


re 

CL - 

re re re re 
CL O O O 


c/) 

L_ 

0 

"3 

Q. 

E 

o 

o 

re 

c 

o 

CO 

L_ 

re 

0. 


co 

-c 

re 

0. 

o 

3 

< 

"O 

re 

■o 


JZ 

o 

re 

CL 


22 "O 


(/) 

re 


o 

o 

O 

0 

0 

C 

o 

0 

(/) 


u 


c 

' 

jC 

3 

re 


m 

0 

L— 

c 

0 

o 

re 

CO 

CD 

0 


>% 

03 

o 

c 

o 

E 

re 

b 

.0 

SI 

Cl 

U) 

re 

re 

■o 

re 

re 

H 

cr 

CO 

0 

L_ 

o 

o 

O 

c 


CO 


o 



Note that for some materials, transportation data were included in the process energy estimates and not provided separately, denoted by "NA" in this table. 






















Exhibit 2-5 

Process GHG Emissions Per Ton of Product Manufactured from Recycled Inputs 




CO 

c 


00 

CM 



O 




CO 

in 

■*fr 

is 

0 

CD 

LO 

05 

00 

00 

CO 

CO 

h- 

0 

eg 

05 

0 

T— 


in 


(/) 


CM 


CD 


CO 

0 

O 

0 

CM 


CO 

co 


in 

0 

O 

T- 

-r_ 

I s - 

0 

00 

O 

CO 

0 

CM 

CO 



0 

o 

</) 

0 

o 

o 

CO 

CO 

LU 

O 

1- 

0 

d 

T_ 

d 

b 

d 

d 

b 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

0 

d 

1- 

k_ 

E 

? 






























CL 
































LU 
































</) 

c 


CM 


O 

O 


O 

O 

0 

0 

0 

0 

0 

0 

0 

0 

O 

0 

0 

0 

0 

0 

0 

0 

0 

T— 

0 

0 

0 

CO 

03 


0 

CM 

O 

0 

CM 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

O 

O 

O 

O 

O 

O 

O 

O 

O 

O 

c/> 

0 

o 

0 

c 

0 

o 

co 

c /3 

LU 

O 

1- 

d 

d 

d 

b 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

b 

d 

d 

d 

d 

d 

d 

d 

k- 

c 


2 





























Q. 

o 

E 































z 

LU 
































</> 

c 


CD 

00 



CO 



^1* 

CO 

in 


IS 

0 

co 

in 

05 

00 

CO 

CO 

CO 

IS 

O 

CM 

05 

0 



in 

</> 



<M 


CD 


0 

0 

0 

0 

CM 


CO 

CO 


m 

0 

0 



IS 

0 

CO 

O 

00 

O 

CM 

CO 



<0 

0 

o 

o 

k_ 

a. 

Energy 

o 

CO 

CO 

E 

(MTCE 

b 

d 


d 

d 

d 

b 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 



LU 

































k. 

tj* 

O 

Tf 

O 

CM 




0 



CM 

CM 

CM 

0 

0 

0 

0 

0 

in 

LO 

0 

LO 

LO 


in 


co 




0 

0 

O 

O 

0 

0 




0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

O 

0 

0 

0 

0 

O 

O 

O 




■*-> 

b 

d 

d 

csi 

d 


r— 

T- 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

b 

d 

d 

d 

d 

b 

d 

CO 




0 






CO 

CO 

CO 




















CM 





r^. 

0 

0 

0 


05 

05 

05 



0 


^ 3 " 


0 

0 

0 

0 

0 

CD 

10 

0 

CD 


CM 


CD 

0 




0 

C\l 

0 

CO 

0 

CM 

0 

O 

0 

0 

T— 

CO 



T— 

0 

0 

O 

0 

0 

CO 

co 

0 

00 

co 

CO 

co 

CM 

O 




_0 

O 

3 

z 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

b 

d 

d 

d 

d 

d 

d 

b 

d 

d 

d 

d 

b 

d 

d 



"0 

k. 



0 

CM 

CO 





0 

05 

05 

CM 

CM 

IS 

0 

05 


IS 


LO 

in 

0 

00 

05 


CD 

05 

LO 



CO 

1^ 

00 


CM 

05 

CO 

CO 

CO 



LO 

T” 

T— 

LO 

0 

CM 

CM 

CM 

■<— 

T— 

T— 

0 

0 

00 


T— 

05 

00 



3 

0 

00 

T— 

CO 

T— 

csi 

d 

d 

d 

d 


d 

CM 

CM 

d 

b 

is 


is 

LO 

csi 

csi 

d 

CM 

cao 


d 

10 

CO 



0 

z 

O 


CM 

CO 

in 

05 

CM 

CM 

CM 


CM 

CO 

CO 

CO 

CM 



LO 

LO 

in 






CM 

T— 

in 

in 





eg 

in 

CO 

05 


CM 

CM 

CM 

0 

CO 

05 

00 

00 

^_ 

0 

O 

00 

00 

00 

in 

LO 

0 

LO 


O 

CM 

05 

CM 




0 

is 

CD 

in 

0 

in 

O 

O 

O 



0 

in 

in 

CD 

0 

O 

CO 

CO 

05 

05 

CD 

0 

05 

05 


05 

CD 

CD 





d 

d 

CM 

d 

d 

d 

d 

d 

06 

IS 

T— 

c\i 

CM 

d 

d 

d 

LO 

LO 

d 

d 

b 

d 

b 

d 

T— 

d 

b 

d 













CO 



CM 

CM 

CM 




■*“ 














>> 

0 

00 

LO 

0 

0 





IS 

in 

CO 

CO 

O 

05 

CD 

00 

00 

CM 

CD 

05 

IS 

in 

05 

O 

00 




cT 




CM 

CD 

is 

T— 

CM 

CM 

CM 

T— 

00 

I s - 

LO 

LO 


CO 

LO 

IS 

1^- 

CO 

CO 

CO 

1^ 


0 

CO 

CD 

CD 

LO 


o> 



LO 

I s -’ 

CM 


in 

CO 

CO 

CO 

T— 

LO 

I s -’ 

CO 

cr> 

d 

CD 

LO 

CO 

CO 

CD 

LO 

LO 

LO 

LO 

IS 

CM 

CD 

05 

T— 


0 

c 


*-* 

0 


I s - 

LO 

CM 


CO 

CO 

CO 

LO 

CM 

LO 

CO 

co 

CO 

is 

CM 



CO 

05 

05 


05 

00 

h- 

00 

CM 



0 

O 

w. 

0 


UJ 






























Q. 



































0 

0 

0 

0 

0 

LO 

LO 

in 

T— 

O 

0 

0 

0 

0 

T— 

CD 

0 

0 

LO 

0 

0 

CO 

O 

0 

O 

0 

O 

O 




(0 

O 

O 

0 

0 

0 

0 

0 

0 

CO 

O 

0 

0 

0 

0 

CO 

LO 

0 

0 

■*— 

0 

0 

eg 

O 

0 

O 

0 

O 

O 


X 


0 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

b 

d 

d 

CO 

co 

d 

d 

b 

b 

d 


d 

d 

d 

d 

d 

d 


s 


5 















CM 







in 








0 

3 

._ 



0 

in 

0 

CO 

00 

00 

00 

0 

LO 

LO 

CM 

CM 

00 

O 

LO 

0 

0 

XT 

CO 

co 

0 

co 

LO 

LO 

CO 


O 


ll 


O 

0 

O 

0 

0 

0 




0 

00 

0 

0 

0 

CO 

0 

0 

0 

0 

05 

0 

0 

0 

0 

0 

0 

0 

0 

0 


0 

0 

k_ 

d 

d 

d 

d 

d 

CM 

CM 

CM 

d 

CM 

d 

d 

d 

CO 

d 

co 

b 

d 

CD 

d 

b 

b 

b 

b 

b 

b 

b 

b 


O) 

E 

X 







T— 



CM 




















u. 

O 

X 






























0 

> 

in 































< 



































00 

CO 

I s - 

0 

CD 




CD 

LO 

0 

CD 

CD 

CM 

O 


0 

0 

in 

CO 

CD 

0 

CD 

CM 

0 

0 

0 

00 



3 

_ 

eg 

0 

CO 

0 

CM 

CM 

CM 

CM 

CD 


CO 

05 

05 

0 

0 

0 

0 

0 


CM 

CM 

0 

CM 

in 

co 

CD 

10 




|0 

0 

3 


d 

CD 

d 

d 

T- 

T— 

T— 

d 

00 

d 

d 

b 

b 

d 

d 

b 

d 

d 

d 

d 

d 

d 

T— 

d 

d 

CD 

d 



</3 

0 

LL 































o: 
































0 


05 

h- 


co 

05 

m 

LO 

LO 

LO 

CM 

00 

CM 

CM 

0 

0 

LO 

IS 

is 

O 

00 

00 

O 

00 

LO 


O 

00 

00 



0 

_ 


O 

00 

CD 

CO 

0 

0 

0 

0 

C') 

ID 

xt; 


CD 

O 

CO 

LO 

LO 

0 

CD 

CD 

0 

CD 

00 

CD 

I s - 





— 

0 

3 

d 

b 

d 

00 

d 

T— 

T- 

T— 

d 

d 

d 

b 

d 

d 

d 

d 

CO 

CO 

d 

d 

d 

d 

d 

d 

d 

b 

CD 

b 



</> 

Q 

LL 































0 


I s - 


0 

0 

CO 

CO 

CO 

LO 


0 


«_ 


0 

O 

0 

0 

0 

0 

0 

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O 

0 


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0. 

O 

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O 

O 

O 

0 

0 

0 

O 

O 

O 

0 

b 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 


0 

0 

O 





-J 

d 

d 

d 

d 

d 

d 

d 

d 

b 

d 

d 

d 

d 

d 

d 

d 

b 

d 

d 

d 

d 

d 

d 

d 

b 

d 

d 

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0 



CO 

0 

in 

CO 

CO 

CO 


CD 

0 

0 

0 


0 

CO 

0 

0 

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CM 

CM 

O 

CM 

O 

co 

O 

CD 

O 





CO 

O 

CO 

O 

LO 

0 

0 

0 

0 


CO 

CM 

CM 

CM 

0 

■<— 

0 

0 

0 



0 


CM 

CM 

CM 

CO 

0 




O 

</> 

d 

d 

b 

d 

d 

d 

d 

d 

b 

d 

d 

b 

d 

d 

b 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 


3 

^ XL 
«/> to m 
<D H' r- 

U o o 
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lo 

cb 


r- o 


°> co 

00 


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CO 


I s - 00 
CD <D 


CM 

CM 

T— 

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05 

10 

LO 

05 


I s - 

■'sf 

T ~ 

O 

LO 


05 



CD 


CM 

0 

b 

c\i 

00 

CO 

d 

b 

b 

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CM 

CO 

b 

CM 

CM 

CO 





in 


CM 



CM 


o 

CM 


0)C0O0)T- 
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IT) C\i O') N cd 

T- T- CO 


</) 

c 

03 

o 


03 

o 

JO 

■O 


CO 

c/3 

0 

o 


03 

o 

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CD 

-Q 

E 

3 


E 

3 

C 


E 

_3 

< 



0 

O 





O 

_L_ 

t 


L_ 

C/3 

(/) 

c 

0 

0 

1 

k_ 

0 

Q. 

CD 

_C 

k_ 

0 

Q. 

c n 

LU 

LU 


TO 

0 

0 

CD 

3 

(/) 

0 

c 

N 

0 

0 

Q. 

0 

Cl 

C/5 

0 

Q. 

0 

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0 

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O 

O 

O 

0 

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Q. 

Q. 

C/5 

Gl 

Q. 

1— 

L_ 

CD 

£ 

O 

O 

0 

O 

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0 

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0 

0 

itz 

JZ 

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O 

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Q. 

O 


z 

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o 

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03 

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c 

0 

E 

b 


=9 -o ® 
LL 0 C 

>>3 I 

IS- 1 

« E 
E 2 
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TO "O 
0 0 
^ ^ b 


*D 

0 

2 0 
co Q- 

<- TO 

E o. 

2 -o 
0 

0 >< 

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0 


E 

o 


XL 

0 

Q_ 


i! 


c 

0 ^ 
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0 o 

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TO if) 


0 


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0 o 

O 

JO c 
X c*= 
O 0 


to Q »- ]T 
2 — <U 
^ TO CL g T3 
^ = TO O O 

O n T1 V- > 


CD 

c 


■O 

■O 

0 

Q_ 


^ 0 
TD CL 
TO m 
0 

o 


o 

0 

CL 


-Q ."2 "g 0 Q 


X 0 x Q. O 
w w 0 0—00 

CO Q GO QC Q. QC 


0 

CL 


0 

o 


2 

o 

0) ^ J 

o o p 
— TO 0 t 
TO O-^o 
O O £ £ 


0 

Ql 


0 

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CL 

0 

< 


0 

0 

C/3 

0 

SZ 

3 

C/5 

0 

V) 

CO 

O 

0 

~o 


0 

0 

cc 

c 0 

_i 

0 

























Exhibit 2-6 

Transportation GHG Emissions Per Ton of Product Manufactured from Recycled Inputs 


c 



CN 

00 




0 

0 

O 

CN 

0 

0 

0 

CN 

CN 

O 

O 


CN 

CN 

O 

CN 

CN 


00 

0 

o 



O 

0 

O 

O 

O 

O 

O 

O 

O 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 


0 

>» 5 


o 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

tr 

o 

a 

</) 

c 

o> .2 

£ .a 

LU E 

LU 

O 

1- 

5 


























0 

V- 

LU 



























L- 






























k. 

0 

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in 

0 

m 

0 

CO 

0 

0 

0 

0 

in 



0 

0 

O 

O 

O 

in 

in 

O 

in 

in 

in 

in 

CN 



0 

O 

0 

O 

0 

O 

O 

O 

O 

0 



0 

0 

0 

O 

0 

0 

0 

0 

0 

0 

0 

0 

0 



0 

d 

d 

0 

d 

d 

d 

O 

d 

d 

d 



d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 

d 



u. 

CN 

0 

CO 

O 

in 

0 

0 

0 


CN 



0 

0 

O 

O 

O 

CO 

CO 

O 

CN 

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Exhibit 2-7 


Retail Transport Energy and Emissions 


Material Type 

Transportatio 
n Energy 
(Million Btu 
Per Ton of 
Product) 

Transportatio 
n Emission 
Factors 
(MTCE per 
Ton of 
Product) 

Aluminum Cans 

0.31 

0.01 

Steel Cans 

0.31 

0.01 

Glass 

1.02 

0.02 

HDPE 

0.48 

0.01 

LDPE 

0.48 

0.01 

PET 

0.48 

0.01 

Corrugated Cardboard 

0.32 

0.01 

Magazines/Third-class Mail 

0.26 

0.01 

Newspaper 

0.26 

0.01 

Office Paper 

0.26 

0.01 

Phonebooks 

1.02 

0.02 

Textbooks 

1.02 

0.02 

Dimensional Lumber 

0.12 

0.00 

Medium-density Fiberboard 

0.32 

0.01 


30 






3. SOURCE REDUCTION AND RECYCLING 


This chapter presents estimates of GHG emissions and carbon sequestration resulting from source 
reduction and recycling of 21 manufactured materials: aluminum cans, steel cans, copper wire, glass, 
plastic containers (LDPE, HDPE, and PET), corrugated cardboard, magazines/third-class mail, 
newspaper, office paper, phonebooks, textbooks, dimensional lumber, medium-density fiberboard, carpet, 
personal computers, clay bricks, concrete, fly ash, and tires. It also presents estimates for s three 
definitions of mixed paper (broad, residential, and office). Also included in this chapter is a discussion of 
forest carbon sequestration, an important input in calculating the emission benefits of paper product 
source reduction and recycling. The chapter is organized as follows: 

Section 3.1 Emission benefits of source reduction; 

Section 3.2 Emission benefits of recycling; 

Section 3.3 Open-loop recycling; 

Section 3.4 Source reduction through material substitution; 

Section 3.5 Implications and methodology of calculating forest carbon sequestration; and 

Section 3.6 Limitations of the analyses presented in this chapter. 

To estimate GHG emissions associated with source reduction and recycling (and other MSW 
management options), EPA used a baseline scenario in which the material is manufactured from the 
current mix of virgin and recycled inputs, but has not yet been disposed of or recycled. Thus, the baseline 
for each material already incorporates some emissions from raw materials acquisition and manufacturing 
using the current mix of virgin and recycled inputs. Using this measurement convention, it follows that 
source reduction 1 reduces GHG emissions from the raw material acquisition and manufacturing phase of 
the life cycle for all materials. Moreover, source reduction of paper results in forest carbon sequestration 
(as discussed in Section 3.5 below). 

Manufacturing from recycled inputs generally requires less energy, and thus lower GHG 
emissions, than manufacturing from virgin inputs. The recycling analysis indicates that recycling reduces 
GHG emissions for each of the materials studied. 

3.1 GHG IMPLICATIONS OF SOURCE REDUCTION 

When a material is source reduced (i.e., less of the material is made), GHG emissions associated 
with making the material and managing the postconsumer waste are avoided. As discussed above, under 
the measurement convention used in this analysis, source reduction has (1) negative raw material and 
manufacturing GHG emissions (i.e., it avoids baseline emissions attributable to current production); (2) 
forest carbon sequestration benefits in the case of paper products (also treated as negative emissions, as 
estimated in Section 3.5); and (3) zero waste management GHG emissions. Exhibit 3-1 presents the GHG 
implications of source reduction. 


1 In this analysis, the values reported for source reduction apply to material lightweighting or extension of a 
product’s useful life. EPA assumes no substitution by another material or product; therefore, EPA assumes no 
offsetting GHG emissions from another material or product. Thus, the data do not directly indicate GHG effects of 
source reduction that involves material substitution. Considerations for estimating the GHG ettects ot material 
substitution are presented in Section 3.4 below. 


31 





In order to compare source reduction to other solid waste management alternatives, EPA 
compared the GHG reductions from source reduction to the life-cycle GHG emissions of another solid 
waste management option (e.g., landfilling). This approach enables policymakers to evaluate, on a per- 
ton basis, the overall difference in GHG emissions between (1) source reducing 1 ton of material, and (2) 
manufacturing and then managing (postconsumer) 1 ton of the same material. Such comparisons are 
made in the Executive Summary and in Chapter 8 of this report. For most materials, source reduction has 
lower GHG emissions than the other waste management options. The most notable exceptions are for 
aluminum cans and carpet, where source reduction benefits are high, but recycling benefits are higher. 

3.2 GHG IMPLICATIONS OF RECYCLING 

When a material is recycled, it is used in place of virgin inputs in the manufacturing process, 
rather than being disposed of and managed as waste. 2 As with source reduction of paper products, 
recycling of paper also results in forest carbon sequestration. 

Most of the materials considered in this analysis are modeled as being recycled in a closed loop 
(e.g., newspaper is recycled into new newspaper). However, a few materials are recycled in an open loop, 
including several paper types (under the general heading of mixed paper) 3 , fly ash, carpet, and personal 
computers (i.e., they are recycled into a product other than themselves); concrete and copper wire are 
recycled in a quasi-open loop. Mixed paper is included because it is recycled in large quantities and is an 
important class of scrap material in many recycling programs. However, presenting a single definition of 
mixed paper is difficult because each mill using recovered paper defines its own supply, which varies 
with the availability and price of different grades of paper. 

For the purpose of this report, EPA identified three definitions for mixed paper: broad, office, and 
residential. To assist recyclers in determining which definition corresponds most closely to mixed paper 
streams they manage, the composition of each is presented in Exhibit 3-2. The broad definition of mixed 
paper includes almost all printing-writing paper, folding boxes, and most paper packaging. Mixed paper 
from offices includes copier and printer paper, stationary and envelopes, and commercial printing. The 
typical mix of papers from residential curbside pick-up includes high-grade office paper, magazines, 
catalogues, commercial printing, folding cartons, and a small amount of old corrugated containers. The 
broad and residential definitions of mixed paper can be remanufactured via an open loop into recycled 
boxboard. Mixed paper from offices is typically used to manufacture commercial paper towels. 

Fly ash is a byproduct of coal combustion that is used as a cement replacement in concrete. The 
analysis for carpet is based on nylon broadloom residential carpet and is a composite of several material 
types, specifically nylon carpet fiber, polypropylene carpet backing, and adhesive of synthetic latex and 
limestone. It is recycled into carpet pad, carpet backing, and molded auto parts. PCs are also composites, 
consisting mostly (by weight) of steel, glass, plastics, aluminum, lead, and copper. They are recycled into 
steel sheet, glass for cathode ray tubes (CRTs), asphalt, aluminum sheet (equivalent to aluminum cans in 
this analysis), lead bullion, and copper wire. Copper wire itself is not recycled specifically into new 
copper wire, but is used in the manufacture of copper alloys. Concrete is crushed and used in place of 
virgin aggregate in the production of new concrete. 


2 

• Note that when paper is manufactured from recycled inputs, the amount of paper sludge produced is greater than 
when paper is made from virgin inputs. This difference is because recycled paper has more short fibers, which must 
be screened out. EPA made a preliminary estimate of the GHG emissions from paper sludge managed in landfills; 
the results indicated that net GHG emissions (i.e., CH 4 emissions minus carbon sequestration) were close to zero. 
Because the emissions are small and highly uncertain, no quantitative estimate is included in this report. 

3 This report also includes estimates for mixed MSW, mixed plastics, mixed organics, and mixed recyclables, i.e., a 
mixture of the principal paper, metal, and plastic materials that are recycled. These other mixed materials are 
discussed in Chapter 8. 


32 



When any material is recovered for recycling, some portion of the recovered material is 
unsuitable for use as a recycled input. This portion is discarded either in the recovery stage or in the 
remanufacturing stage. Consequently, less than 1 ton of new material generally is made from 1 ton of 
recovered material. Material losses are quantified and translated into loss rates. In this analysis, EPA 
used estimates of loss rates provided by FAL for steel, dimensional lumber, and medium-density 
fiberboard (the same materials for which FAL’s energy data were used, as described in Chapter 2). ORD 
provided loss rates for the other materials. These values are shown in Exhibit 3-3 

GHG emission reductions associated with remanufacture using recycled inputs are calculated by 
taking the difference between (1) the GHG emissions from manufacturing a material from 100 percent 
recycled inputs, and (2) the GHG emissions from manufacturing an equivalent amount of the material 
(accounting for loss rates) from 100 percent virgin inputs. 

The results of the analysis are shown in Exhibit 3-8. In this exhibit, for each material the 
differences between manufacture from virgin and recycled inputs for (1) energy-related GHG emissions 
(both in manufacturing processes and transportation), (2) process nonenergy-related GHG emissions, and 
(3) forest carbon sequestration are presented. The method of accounting for loss rates yields estimates of 
GHG emissions on the basis of MTCE per short ton of material recovered for recycling (rather than 
emissions per ton of material made with recycled inputs). 

EPA recognizes that some readers may find it more useful to evaluate recycling in terms of tons 
of recyclables as marketed (after sorting and processing) rather than tons of materials recovered. To 
adjust the emission factors reported in Exhibit 3-8 for that purpose, one would scale up the recycled input 
credits shown in columns “b” and “d” of that exhibit by the ratio of manufacturing loss rate to total loss 
rate (i.e., Exhibit 3-3 column “c” divided by column k ‘d”). 

Another way that recycling projects can be measured is in terms of changes in recycled content of 
products. To evaluate the effects of such projects, one could use the following algorithm: 4 

(Eqn. 1) 


T recyc - Tprod x (RC p -RCj)/L 

Where, 

Trecyc = tons of material recycled, as collected 

Tprod = tons of the product with recycled content 

RC P = recycled content (in percent) after implementation of the project 

RQ = recycled content (in percent) initially 

L = loss rate (from Exhibit 3-3, column “d”) 

Then, one could use the emission factors in this report directly with the tons of material recycled 
(as collected) to estimate GHG emissions. 


4 This approach would apply only where the products with recycled content involve the same recycling loop as 
the ones on which the values in this report are based (e.g., aluminum cans are recycled in a closed loop into more 
aluminum cans). 


33 



Exhibit 3-1 

GHG Emissions for Source Reduction 
(MTCE/Ton of Material Source Reduced) 



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0 


0 

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E 

TO 


CD 

O 

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0 

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CD 

C 

0 

TO 

E 

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d 

0 


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CL 


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i— 

0 

TO 

CL 

E 

o 

O 

"to 

c 

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CD 


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TO 0 
O X 


CD 

O 0 

£ £ 

>» g 
JS o 
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CD 

< CD 

>4 l_ 


r< 















Exhibit 3-2 

Composition of Mixed Paper Categories (As a Percentage of Total) 


Paper Grade 

All Paper and 
Paperboard in 
MSW a 

Mixed Paper: Broad 
Definition b 

Mixed Paper: 
Office c 

Mixed Paper: 
Single-Family 
Residential d 

Uncoated groundwood paper 

4.9% 

4.9% 

7.9% 

2.2% 

Coated free sheet paper 

5.0% 

12.0% 

13.9% 

11.5% 

Coated groundwood paper 

4.3% 

11.5% 

30.7% 

17.7% 

Uncoated free sheet paper 

14.3% 

37.6% 

41.6% 

18.4% 

Cotton fiber paper 

0.1% 

0.4% 

1.8% 

0.2% 

Bleached bristols 

1.5% 

3.9% 

4.1% 

2.8% 

Newspaper 

13.3% 

2.9% 


2.9% 

Virgin corrugated boxes 

29.6% 



12.2% 

Recycled corrugated boxes 

6.8% 



2.8% 

Unbleached kraft folding boxes 

1.5% 

5.7% 


4.1% 

Bleached kraft folding boxes 

2.8% 

5.7% 


5.8% 

Recycled folding boxes 

3.0% 

7.9% 


8.0% 

Bleached bags and sacks 

0.4% 

1.0% 


1.6% 

Unbleached bags and sacks 

2.1% 

5.6% 


9.0% 

Unbleached wrapping paper 

0.1% 

0.2% 



Converting paper 

0.3% 




Special industrial paper 

1.3% 




Other paperboard 

2.5% 




Paper plates and cups 

1.2% 




Tissue, towels 

3.9% 




Set-up boxes 

0.3% 

0.7% 


0.6% 

Other paper packaging 

0.8% 




Totals 

100.0% 

100.0% 

100.0% 

100.0% 


a All grades of paper and paperboard in MSW. 

b Excludes newspaper, old corrugated containers, tissue produce, paper plates and cups, converting and special industrial papers, 
nonpackaging paperboard such as album covers and posterboard, and paper labels. 

c Includes the high-grade papers (ledger and computer printout) as well as stationery, mail, magazines, and manila folders. Could 
be recovered as “file stock.” 

d Represents a typical collection of mixed paper from a single-family curbside program. Includes printing-writing papers, 
corrugated boxes, folding cartons, and bags and sacks. 

Source: Working papers prepared by Franklin Associates, Ltd., October 1997. 

In order to compare GHG emissions from recycling to those attributable to another solid waste 
management option such as landfilling, EPA compared the total GHG emissions from recycling the 
material to the GHG emissions from managing the disposal of the same material under another waste 
management option. The baseline for a given material (which includes GHG emissions from raw 
materials acquisition and manufacturing for the current mix of virgin and recycled inputs) for both 
options is the same. Overall, because recycling reduces the amount of energy required to manufacture 
materials (as compared to manufacture with virgin inputs) and leads to avoided process nonenergy GHG 
emissions, recycling has lower GHG emissions than all other waste management options except tor 
source reduction. 


35 
































Exhibit 3-3 

Loss Rates For Recovered Materials 


(a) 

(b) 

(c) 

(d) 

(e) 




(d = b x c) 




Tons of Product 

Tons of 



Percent of 

Made per Ton of 

Product 



Recovered 

Recycled Inputs 

Made Per 



Materials 

In the 

Ton 



Retained in the 

Manufacturing 

Recovered 

Data 

Material 

Recovery Stage 

Stage 

Materials 

Source 3 

Aluminum Cans 

100 

0.93 

0.93 

FAL & ORD 

Steel Cans 

100 

0.98 

0.98 

FAL 

Copper Wire 

82 

0.99 

0.81 

FAL 

Glass 

90 

0.98 

0.88 

FAL & ORD 

HDPE 

90 

0.86 

0.78 

FAL & ORD 

LDPE 

90 

0.86 

0.78 

FAL & ORD 

PET 

90 

0.86 

0.78 

FAL & ORD 

Corrugated Cardboard 

100 

0.93 

0.93 

FAL & ORD 

Magazines/Third-class Mail 

95 

0.71 

0.67 

FAL & ORD 

Newspaper 

95 

0.94 

0.90 

FAL & ORD 

Office Paper 

91 

0.66 

0.60 

FAL & ORD 

Phonebooks 

95 

0.71 

0.68 

FAL & ORD 

Textbooks 

95 

0.69 

0.66 

FAL & ORD 

Dimensional Lumber 

88 

0.91 

0.80 

FAL 

Medium-density Fiberboard 

88 

0.91 

0.80 

FAL 

Tires b 

90 

0.86 

0.78 

NA 

a FAL provided data for column (b), while ORD provided data 

for column (c). 


used as a proxy. 

Explanatory notes: The value in column “b” accounts for losses such as recovered newspapers that were unsuitable for 
recycling because they were too wet. Column “c” reflects process waste losses at the manufacturing plant or mill. 

Column “d” is the product of the values in Columns “b” and “c.” 

3.3 OPEN-LOOP RECYCLING 

Unlike most of the materials for which EPA has developed recycling GHG emission factors (e.g., 
aluminum cans, glass bottles), some materials are assumed to be recycled in an “open loop”—i.e., carpet 
is recycled into new products other than new carpet. Therefore, the GHG benefits of some material 
recycling result from the avoided emissions associated with the manufacture of the secondcny products 
that the material is recycled into (since the recycling would affect only the production of the secondary 
products). In applying this method, EPA considered only the GHG benefit for one generation of 
recycling (i.e., future benefits from recycling the secondary products into additional products were not 
included). To calculate the GHG benefits of recycling the primary material, EPA compared the difference 
in emissions associated with manufacturing one ton of each of the secondary products from virgin versus 
recycled materials, after accounting for losses that occur in the recycling process. The results for each of 
the secondary products then were weighted by the appropriate material-flow distribution to obtain a 
composite emission factor for recycling the primary material type. Materials that are recycled in an open- 
loop fashion within EPA’s life-cycle methodology are mixed paper and corrugated cardboard, copper 
wire, carpet, personal computers, and concrete. 

The secondary product resulting from recycling mixed paper is typically boxboard. This use of 
mixed paper is due to quality constraints related to a broad mixture of paper types that include newsprint, 
office paper, coated paper, and corrugated paper. The pulp fibers obtained from mixed paper are well 
suited for lower grade forest product such as cardboard. For the purposes of this methodology, EPA 
assumed that 100 percent of recycled mixed paper is utilized to produce boxboard. When corrugated 




36 











cardboard is recycled, it is assumed that 74 percent is used to produce boxboard and the remaining 26 
percent is utilized to produce corrugated cardboard. In this sense corrugated cardboard is recycled in a 
partial open loop. Data for creating the open loops for mixed paper and corrugated cardboard were 
obtained through consultation with the Recycled Paper Trade Association (RPTA). 

Secondary products resulting from carpet recycling include carpet pad, molded products, and 
carpet backing. Carpet pad is used as a cushion layer between the carpet and the floor, which provides 
thermal and acoustical insulation, and resilience. Molded products for automobiles are used in a wide 
range of applications, from air intake assemblies to headrests. The carpet backing produced from 
recycled carpet is generally used to secure the yam and provide dimensional stability to commercial 
carpeting. While current information on this subject is not readily available, the use of recycled material 
is believed to have become both higher and more widespread. An advantage to recycling carpet into 
backing is that it uses 100 percent of the materials from the recovered carpet, thereby avoiding a solid 
waste stream from the recycling process. For details on the recycling life-cycle analysis for carpet, please 
review the Background Document for Life-Cycle Greenhouse Gas Emission Factors for Carpet and 
Personal Computers. ~ 

When PCs are recycled, they may be recycled into asphalt, steel sheet, lead bullion, CRT glass, 
copper wire, and aluminum sheet. Recovered plastic can be utilized as a filler component in the 
production of asphalt for road construction. Steel and aluminum sheet are used to produce a wide range 
of materials from auto parts to cookware. Recovered CRT glass can be utilized for the production of new 
CRT screens or processed to recover lead bullion that can be used to produce items such as batteries and 
x-ray shielding. Copper wire can be utilized in various electrical applications depending on its grade. For 
details on the recycling life-cycle analysis for personal computers, please review the Background 
Document for Life-Cycle Greenhouse Gas Emission Factors for Carpet and Personal Computers. 5 6 

Copper wire is the most common form of unalloyed copper recycled from a municipal solid waste 
perspective. Given the very high virgin content of copper wire (due to purity standards), it is likely that 
recovered copper wire would in most cases go into lower grade copper alloys. 7 8 Therefore, the most 
accurate approach would be to determine the energy/emissions associated with the production of smelted 
copper (ingot), rather than finished copper wire. For details on the recycling life-cycle analysis for 
copper wire, please review the Background Document for Life-Cycle Greenhouse Gas Emission Factors 
for Copper Wire. 6 

When concrete structures are demolished, the waste concrete can be crushed and reused in place 
of virgin aggregate. Doing so reduces the GHG emissions associated with producing concrete using 
virgin aggregate material. Virgin aggregates, which include crushed stone, gravel, and sand, are used in a 
wide variety of construction applications, such as road base, fill, and as an ingredient in concrete and 
asphalt pavement. For details on the recycling life-cycle analysis for concrete, please review the 
Background Document for Life-Cycle Greenhouse Gas Emission Factors for Clay Brick Reuse and 
Concrete Recycling . 9 

Coal-based electricity generation results in the production of significant quantities of coal 
combustion products (CCPs). Fly ash is a CCP that possesses unique characteristics that allow it to be 


5 Available at the EPA, Global Warming—Waste, “Solid Waste Management and Greenhouse Gases” website. Go 
to: http://www.epa.gov/mswchmate, then follow links to Publications -> Reports, Papers, and Presentations -> This 
report -> Background Documents. 

6 Ibid. 

7 CD A, 2003. Technical Report: Copper , Brass, Bronze. The U.S. Copper-base Scrap Industry and Its Byproducts. 
Copper Development Association, Inc. 

8 Available at the EPA, Global Warming—Waste, “Solid Waste Management and Greenhouse Gases” website. Op 
cit. 

9 Ibid. 


37 




utilized as a substitute for Portland cement in making concrete. Through the reuse of fly ash, the GHG 
emissions associated with the production of Portland cement are avoided. For details on the recycling 
life-cycle analysis for concrete, please review the Background Document for Life-Cycle Greenhouse Gas 
Emission Factors for Fly Ash Used as a Cement Replacement in Concrete. 10 

3.4 SOURCE REDUCTION THROUGH MATERIAL SUBSTITUTION 

As noted above, the analysis of source reduction is based on an assumption that source reduction 
is achieved by practices such as lightweighting, double-sided copying, and material reuse. However, it is 
also possible to source reduce one type of material by substituting another material. Analyzing the GHG 
impacts of this type of source reduction becomes more complicated. Essentially, one would need to 
estimate the net GHG impacts of (1) source reduction of the original material, and (2) manufacture of the 
substitute material and its disposal fate. A quantitative analysis of source reduction with material 
substitution was beyond the scope of this report because of the large number of materials that could be 
substituted for the materials analyzed in this report (including composite materials, e.g., a composite of 
paper and plastic used in juice boxes) and the need for application-specific data. Where both the original 
material and the substitute material are addressed in this report, however, the GHG impacts of source 
reduction with material substitution may be estimated. 

The estimate would be based on (1) the data provided in this report for the material that is source 
reduced; (2) the mass substitution rate for the material that is substituted; and (3) data in this report for the 
material substituted. The mass substitution rate is the number of tons of substitute material used per ton 
of original material source reduced. Note, however, that in calculating the mass substitution rate, one 
should account for any difference in the number of times that a product made from the original material is 
used prior to waste management, compared to the number of times a product made from the substitute 
material will be used prior to waste management. 

To estimate the GHG impacts of source reduction with material substitution (per ton of material 
source reduced), one should consider the following: a specific baseline scenario, including waste 
management; an alternative scenario, involving the substitute material and a waste management method; 
the number of tons of material used in each scenario, using the mass substitution rate; the net GHG 
emissions for the baseline; the GHG impacts of source reduction of the original material; the GHG 
impacts of manufacturing the substitute material; and the GHG impacts of waste management for the 
substitute material. Among other factors, these considerations will allow for a comparison of net GHG 
emissions from source reduction with material substitution to the baseline. 

3.5 FOREST CARBON SEQUESTRATION 

As forests are planted and allowed to grow, they absorb atmospheric C0 2 and store it in the form 
of cellulose and other materials. When the rate of uptake exceeds the rate of release, carbon is said to be 
sequestered. On the other hand, when trees are cleared and processed or burned, carbon is released. 

When paper and wood products are recycled or source reduced, trees that would otherwise be 
harvested are left standing. In the short term, this reduction in harvesting results in a larger quantity of 
carbon remaining sequestered, because the standing trees continue to store carbon, whereas the 
manufacture and use of paper and wood products tend to release carbon." In the long term, some of the 
short-term benefits disappear as market forces result in less planting of new managed forests than would 


10 Ibid. 

11 The forest carbon inventory in any year equals the carbon inventory the year before, plus net growth, minus 
harvests, minus decay. Thus, when harvests are reduced, the inventory increases. However when inventories 
become high relative to the carrying capacity of the land, the rate of growth decreases because net growth (the rate 
at which growth exceeds decay) declines. 


38 



otherwise occur, so that there is comparatively less forest acreage in trees that are growing rapidly (and 
thus sequestering carbon rapidly). 

In the United States, uptake by forests has long exceeded release, influenced by forest 
management activities and the reforestation of previously cleared areas. This net sequestration of carbon 
in forests represents a large and important process. EPA estimated that the annual net C0 2 flux (i.e., the 
excess of uptake minus release) in U.S. forests was about 213 MMTCE in 2004, 12 offsetting about 8 
percent of U.S. energy-related C0 2 emissions. In addition, about 16 million metric tons of carbon was 
stored in wood products currently in use (e.g., wood in building structures and furniture, paper in books 
and periodicals). Considering the effect of forest carbon sequestration on U.S. net GHG emissions, it was 
clear that a thorough examination was warranted for this study. 

EPA worked with the U.S. Department of Agriculture Forest Service (USDA-FS) to use models 
of the U.S. forest sector to estimate the amount of forest carbon sequestration per incremental ton of paper 
reduced and recycled. These USDA-FS models and data sets are the most thoroughly documented and 
peer-reviewed models available for characterizing and simulating the species composition, inventory, and 
growth of forests, and they have been used to analyze GHG mitigation in support of a variety of policy 
analyses conducted by the Forest Service, so they represent the current state-of-the-art. 

EPA used an approach that modeled (1) the effect of incremental recycling on wood harvests, and 
(2) the change in forest carbon stocks as a function of marginal changes to harvest rates, using the 
FORCARB II model, and combined the two components to estimate the effect of recycling on forest 
carbon storage. EPA found that increased recycling of paper products resulted in incremental forest 
carbon storage of about 0.55 MTCE per ton of paper recovered for mechanical pulp papers and 0.83 
MTCE per ton of paper recovered for chemical pulp papers. Papers made from mechanical pulp include 
newspaper, telephone books, and magazines/third-class mail; papers made from chemical pulp include 
office paper, corrugated cardboard, and textbooks. The approach to modeling the impact of source 
reduction and recycling on forest carbon stocks has changed since the last edition of this report was 
published. The revised approach includes the use of updated USDA-FS models and the differentiation of 
chemical and mechanical pulp papers. 

The USDA-FS models do not directly estimate the effect of source reduction on forest carbon 
storage. To derive these estimates, EPA evaluated the mix of virgin and recycled inputs used to 
manufacture each material. As described later, this mix is different for each product. The resulting 
carbon sequestration rates are 1.04 MTCE per ton for mechanical pulp papers to 1.98 MTCE per ton for 
chemical pulp papers for 100 percent virgin inputs, and they range from 0.80 to 1.90 MTCE per ton for 
various paper grades for the current mix of inputs. 

3.5.1 Effect of Paper Recovery on Pulpwood Harvest 

Several earlier USDA-FS efforts have analyzed the relationship between paper recovery rates and 
pulpwood harvests, based on data compiled by the American Forest and Paper Association (AF&PA) and 
the Forest Resources Association (FRA). AF&PA collects information on the mass of recovered paper 
and wood pulp consumed 1 ' and paper and paperboard production. 14 FRA publishes information on 
pulpwood receipts. 15 Using assumptions on the moisture content of pulpwood receipts (as harvested, 50 
percent), paper, and paperboard (3 percent), wood pulp consumed (10 percent), and recovered paper 
consumed (15 percent). Dr. Peter Ince of USDA-FS developed the following relationship: 


12 EPA. 2006. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004. U.S. Environmental Protection 
Agency, Office of Air and Radiation, Washington, DC. EPA- 430-R-06-002. 

13 AF&PA. 2005. Wood pulp, recovered paper, pulpwood 25 th Annual survey, 2004-2007. Washington, DC. 

14 AF&PA, 2004. 2004 Statistics—Paper, paperboard and wood pulp. Washington, DC. 

15 FRA, 2004. Annual pulpwood statistics summary report, 1999-2003. Rockville, MD. 


39 



PWH= X x (PP - [PR x {1-EX} x Y]) 


(Eqn. 2) 


Where, 

PWH = pulpwood harvests at 0 percent moisture content, i.e., ovendry (tons) 

PP = paper production at 3 percent moisture content (tons) 

PR = paper recovery at 15 percent moisture content (tons) 

EX = percent of recovered paper that is exported (%) 

X = process efficiency of converting ovendry pulpwood to paper and paperboard at 3 percent 
moisture content. It is the ratio of finished paper to puip, and accounts tor the portion of 
paper and paperboard that is water and fillers 

Y = process efficiency of converting recovered paper at 15 moisture to paper and paperboard 
at 3 percent moisture. It is the ratio of recovered paper to finished paper, and accounts 
for the water in recovered paper. 

The values of X and Y are based on process yield estimates provided by John Klungness 
(Research Chemical Engineer, USDA-FS) and Ken Skog (Project Leader, Timber Demand and 
Technology Assessment Research, USDA-FS). The value for EX, the export rate, is based on examining 
total paper recovery and exports over the last 10 years for which data were available (1995-2004). Given 
that our focus is on the effect of small changes in paper recovery, it is more appropriate to focus on the 
marginal ratio of exports to paper recovery (rather than the average ratio). Thus, EPA calculated the 
change in annual exports for the end of the period compared to the beginning (3.23 million tons) and 
divided this figure by the change in annual paper recovery for the end of the period compared to the 
beginning (8.1 million tons), yielding a value of 40 percent. EPA used 40 percent as the export rate for 
both types of paper (mechanical and chemical). 

As shown in Exhibit 3-4, the avoided pulpwood harvest is 0.58 tons per ton paper recovered for 
mechanical pulp papers, and 0.89 tons per ton paper recovered for chemical pulp papers. 


Exhibit 3-4 

Relationship Between Paper Recovery and Pulpwood Harvest (Values of Eqn. 2 Parameters) 



a 

b (= 1 / a) 

c 

Y = Ratio of 

d 

e (= b x c x [1 - d]) 


Ratio of Pulp 

X = 

Recovered Paper 


Avoided Tons PWH 


to Finished 

Process 

to Finished 


per Ton Paper 


Paper 

Efficiency 

Paper 

EX 

Recovered 

Mechanical Pulp 

0.900 

1.11 

0.875 

40% 

0.58 

Chemical Pulp 

0.475 

2.11 

0.700 

40% 

0.89 


3.5.2 The Effect of Change in Pulpwood Harvest on Forest Carbon—FORCARB II 
Analysis 

FORCARB II simulates the complex, dynamic nature of forest systems, including the interaction of 
various forest carbon pools, how carbon stocks in those pools change over time, and whether the response 
of forest carbon is linearly proportional to harvests. To explore these questions, USDA-FS ran two 
enhanced recycling/reduced pulpwood harvest scenarios in FORCARB II. The base assumptions on 
pulpwood harvests are derived from NAPAP (North American Pulp and Paper) Model baseline 
projections developed for the Forest Service 2001 RPA Timber Assessment. The two reduced harvest 
scenarios involved decreasing pulpwood harvest by 6.7 million tons and 20.2 million tons for the period 
2005-2009. Harvests in all other periods were the same as the baseline. 

For each scenario, EPA calculated the delta in carbon stocks with respect to the base case—this 
represents the carbon benefit of reduced harvests associated with recycling. The change in carbon was 
divided by the incremental tons of pulpwood harvested to yield results in units of MTCE per metric ton 
pulpwood not harvested, i.e., the carbon storage rate. 


40 









As shown in Exhibit 3-5, the carbon storage rate starts at about 0.99 MTCE per metric ton 
pulpwood in 2010, increases to about 1.08 MTCE per metric ton pulpwood in 2030, and declines with 
time to about 0.82 MTCE Carbon per metric ton pulpwood in 2050. The exhibit also shows that across 
the two incremental recovery scenarios, the carbon storage rate (per unit paper recovered) was virtually 
identical. 


Exhibit 3-5 Increased Forest Carbon Storage per Unit of Reduced Pulpwood Harvest 


Forest C Storage 


TD 

O 

o 


§ 


a. 

a. 

QJ 

c 

c 


o 


O 

a> 

c 

c 

o 



-♦— 6.7 Mton 
Reduction in 
Pulpw ood 
Harvest 
■■—20.1 Mton 
Reduction in 
Rjlpw ood 
Harvest 


The use of the FORCARB II model allowed analysis of the timing and magnitude of changes in 
specific carbon pools within the forest. As shown in Exhibit 3-6, the primary effect of reduced pulpwood 
harvests was to increase the total live tree pool. This effect was offset to some degree by a decrease in the 
total downed wood pool. Carbon in the total dead tree, forest floor, and understory pools increased 
slightly; there was no effect on the soil pool. Most of the deltas peaked in 2010 and moderated somewhat 
over the next 40 years, though forest floor has more of a lag; the delta peaked in 2030. Both of those 
pools responded quickly to the change in harvests (which occurred for the 2005-2009 period). It appears 
that the major driver of the net carbon storage estimate is the time it took for the competing effects in the 
live tree and total downed wood pools to decline back to the baseline levels; since the total downed wood 
pool returns to baseline levels more quickly than the Live Tree pool, the net actually increased through 
2030. 

The FORCARB II results indicate that the effect of paper recycling on carbon storage appears to be 
persistent (i.e., lasting at least for several decades). EPA chose to use the value for 2020 for use in the 
emission factors, viz., 1.04 MTCE per metric ton pulpwood. The choice of 2020 represents a delay of 
about 5 to 15 years with respect to the onset of incremental recycling, long enough to reflect the effects of 
the recycling program, but lower than the peak effect in 2030. As shown above, the effect is relatively 
stable over time, so the choice of year does not have a significant effect. 


41 


























Exhibit 3-6 Change, with respect to baseline, in carbon stocks for FORCARB II pools 


Delta, C Pools, -6,7 Mtons Pulpwood Harvest 



♦—TOTAL LIVE TREE 
TOTAL DEAD TREE 
*— TOTAL DOWNED WOOD 
— SOIL 

--FOREST FLOOR 

UNDERSTORY 
-■— Net across pools 


For additional details on this methodology and a comparison of the FORCARB II results to those 
from other analyses, please see the Background Document on the Effect of Paper Recycling on Forest 
Carbon . 16 

3.5.3 Effect of Change in Paper Recovery on Forest Carbon 

To estimate the rate of forest carbon change per ton of paper recovery, one can multiply the rate 
of pulpwood harvest (PWH) per ton of paper recovery (PRC) by the rate of forest carbon (FC) change per 
ton of pulpwood harvest, as shown below: 

For mechanical pulp, 

0.58 metric ton PWH per metric ton PRC x 1.04 metric ton FC/metric ton PWH = 0.61 metric ton 

FC/metric ton PRC 

For chemical pulp, 

0.89 metric ton PWH per metric ton PRC x 1.04 metric ton FC/metric ton PWH = 0.92 metric ton 

FC/metric ton PRC 

Converting to rates of metric tones forest carbon per short ton of paper (to be consistent with 
units used throughout this report), the values are 0.55 metric ton FC/ton PRC and 0.83 metric ton FC/ton 
PRC for mechanical and chemical pulps, respectively. The various paper grades fall into mechanical or 
chemical pulp categories as follows: 

• Mechanical pulp papers—newsprint, telephone books, magazines/third class mail 

• Chemical pulp papers—office paper, corrugated cardboard, textbooks 


16 Available at the EPA, Global Warming—Waste, “Solid Waste Management and Greenhouse Gases” website. Op 
cit. 


42 

























3.5.4 Effect of Source Reduction on Carbon Stocks 

EPA estimated source reduction values under two assumptions: that source reduction displaces 
only virgin inputs, and that it displaces the current mix of virgin and recycled inputs. 17 For the first 
assumption, 100 percent virgin inputs, EPA used the process efficiency (X) values described in Section 
3.5.1 to calculate the amount of pulpwood harvest reduced per ton of paper source reduction. Those 
values are 1.11 metric ton PWH per metric ton and 2.11 metric ton PWH per metric ton for mechanical 
and chemical pulps, respectively (as shown in Exhibit 3-4). Multiplying these values by the rate of forest 
carbon storage per ton of reduced PWH (1.04 MTCE per ton PWH), and converting to short tons, source 
reduction of mechanical pulp papers manufactured from 100 percent virgin pulp would increase forest 
carbon storage by 1.04 MTCE per ton, and for chemical pulp papers, 1.98 MTCE per ton. These values 
are shown in column (d) of Exhibit 3-7. 

The second scenario involves the assumption that source reduction would affect production using 
the current mix of virgin and recycled inputs. Given that displacing recycled inputs would not influence 
forest carbon per se, in this scenario the forest carbon effect is only attributable to the proportion of inputs 
that comprise virgin pulp, as shown in column (e) of Exhibit 3-7. The values in column (f) show the 
result of multiplying the virgin proportion in the current mix by the forest carbon benefit per ton of 100 
percent virgin inputs. 


Exhi 

bit 3-7 Forest Carbon Storage from Recycling 

and Source Reduction 

(a) 

(b) 

(c) 

(d) 

(e) 

(f) 

Material 

Mechanical 
(M) or 

Chemical (C) 

Recycling, 

(MTCE/ton) 

Source 
Reduction, 
100% Virgin 
Inputs 
(MTCE/ton) 

Percent 
Virgin Inputs 
in the Current 
Mix of Inputs 

(f = dx e ) 

Source Reduction, 
Current Mix 
(MTCE/ton) 

Corrugated 

Cardboard 

C 

0.83 

1.98 

65.1% 

1.29 

Magazines/Third- 
class Mail 

M 

0.55 

1.04 

95.9% 

1.00 

Newspaper 

M 

0.55 

1.04 

77.0% 

0.80 

Office Paper 

C 

0.83 

1.98 

95.9% 

1.90 

Phonebooks 

M 

0.55 

1.04 

100.0% 

1.04 

Textbooks 

C 

0.83 

1.98 

95.9% 

1.90 


17 Source reduction may conceivably displace 100 percent virgin inputs if the quantity of paper recovered does not 
change with source reduction, and all recovered paper is used to make new paper. In that case, if the quantity ot 
paper manufactured is reduced through source reduction, all of the reduction in inputs would come from virgin 
inputs. It is more likely, however, that source reduction reduces both virgin and recycled inputs. In fact, because 
source reduction would result in less used product being available to recover, it may have a greater ettect on 
recovered fiber use than on virgin fiber. Thus, even the current mix scenario may represent the high end of the range 
of effects on forest carbon storage. 


43 













3.5.5 Limitations and Uncertainties of the Forest Carbon Analysis 

There are several limitations associated with the analysis. The forest product market is very 
complex, and EPA’s simulation of some of the underlying economic relationships that affect the market 
simplifies some important interactions. 

As noted earlier, the results are very sensitive to the assumption on paper exports (i.e., that paper 
exports comprise a constant proportion of total paper recovery). If all of the recovered paper is exported, 
none of the incremental recovery results in a corresponding reduction in U.S. pulpwood harvest. At the 
other extreme, if all of the incremental recovery results in a corresponding reduction in U.S. pulpwood 
harvest, the storage factor would be higher. The results are also sensitive to assumptions on the moisture 
content and the carbon content of pulpwood, pulp, and paper. 

Also, this analysis does not consider the effect that decreases in pulpwood harvest may have on 
the supply curve for sawtimber, which could result in a potential increase in harvests of other wood 
products. This could result in a smaller reduction in harvest, offsetting some of the carbon storage benefit 
estimated here. Prestamon and Wear IN investigated how pulpwood and sawtimber supply would change 
with changes in prices for each. They estimated that non-industrial private forest and industry may 
increase sawtimber supply when price for pulpwood increases—and the change is perceived as 
temporary—although the estimate was not statistically significant. But the sawtimber supply may 
decrease when pulpwood price increases—and the change is perceived as permanent—but once again the 
estimate was not statistically significant. Given that the relationship between the price change for 
pulpwood and supply of sawtimber was not consistent and was often statistically insignificant, there was 
not compelling evidence to indicate that the omission of this effect is a significant limitation to the 
analysis. 

A related issue is that if there is a decrease in the domestic harvest of pulpwood, it could result in 
a decrease in the cost of domestic production, which could shift the balance between domestic paper 
production and imports to meet demand. 

Another limitation of the analysis is that it did not account for any potential long-term changes in 
land use due to a reduction in pulpwood demand, and landowners’ choices to change land use from 
silviculture to other uses. If overall forest area is reduced, this would result in significant loss of carbon 
stocks. Hardie and Parks 19 developed an area base model for use in Resource Planning Act assessments 
to help determine factors that influence land area change. They derived a model that estimated the 
elasticity of forest land area change with respect to pulpwood price change. They estimated the elasticity 
to be -0.10 but this was not significant at the 10 percent confidence level. This suggests that forest area 
change would be limited with a modest price change in pulpwood demand. 

In summary, there are several limitations and uncertainties associated with the analysis, but they 
are generally less significant compared to the uncertainty associated with the question of how much paper 
is exported. Despite the limitations and uncertainties, this analysis provides a reasonable approximation 
of the effects that increased paper recovery would have on forest carbon stocks. 


18 J.P. Prestamon and D.N. Wear. 2000. Linking Harvest Choices to Timber Supply. Forest Science 46 (3)- 377- 
389. 

14 1.W. Hardie and P.J. Parks. 1997. Land Use with Heterogeneous Land Quality: An Application of an Area Base 
Model. American Journal of Agricultural Economics 79:299-310. 


44 



3.6 LIMITATIONS 


Because the data presented in this chapter were developed earlier in Chapter 2, the limitations 
discussed in those chapters also apply to the values presented here. Other limitations are as follows: 

• There may be GHG impacts from disposal of industrial wastes, particularly paper sludge at paper 
mills. Because of the complexity of analyzing these second-order effects and the lack of data, 
EPA did not include them. A screening analysis for paper sludge was performed based on (1) 
data on sludge generation rates and sludge composition (i.e., percentage of cellulose, 
hemicellulose, lignin, etc. in sludge),and (2) professional judgment on the CH 4 generation rates 
for cellulose, etc. The screening analysis indicated that net GHG emissions (CH 4 emissions 
minus carbon storage) from paper sludge are probably on the order of 0.00 MTCE per ton of 
paper made from virgin inputs to 0.01 MTCE per ton for recycled inputs. The worst case 
bounding assumptions indicated maximum possible net GHG emissions ranging from 0.03 to 

0.11 MTCE per ton of paper (depending on the type of paper and whether virgin or recycled 
inputs are used). 

• The recycling results are reported in terms of GHG emissions per ton of material collected for 
recycling. Thus, the emission factors incorporate assumptions on loss of material through 
collection, sorting, and remanufacturing. There is uncertainty in the loss rates: some materials 
recovery facilities and manufacturing processes may recover or use recycled materials more or 
less efficiently than estimated here. 

• The models used to evaluate forest carbon sequestration and those used to evaluate energy and 
nonenergy emissions differ in their methods for accounting for loss rates. Although one can 
directly adjust the emission factors reported here for process emissions so that they apply to tons 
of materials as marketed (rather than tons as collected), there is no straightforward way to adjust 
the forest carbon estimate. 

• Because the modeling approach assumes closed-loop recycling for all materials except mixed 
paper, it does not fully reflect the prevalence and diversity of open-loop recycling. Most of the 
materials in the analysis are recycled into a variety of manufactured products, not just into the 
original material. Resource limitations prevent an exhaustive analysis of all the recycling 
possibilities for each of the materials analyzed. 

• For the purpose of simplicity, EPA assumed that increased recycling does not change overall 
demand for products. In other words, it was assumed that each incremental ton of recycled inputs 
would displace virgin inputs in the manufacturing sector. In reality, there may be a relationship 
between recycling and demand for products with recycled content, since these products become 
cheaper as the supply of recycled materials increases. 


20 ICF Consulting. 1996. Memorandum to EPA Office of Solid Waste, “Methane Generation from Paper Sludge,” 
December. 


45 



Exhibit 3-8 

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inputs rather than virgin inputs. The credit accounts for loss rates in collection, processing, and remanufacturing. Recycling credit is based on closed- and open-loop recycling depending on 
material. 













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48 


4. COMPOSTING 


This chapter presents estimates of GHG emissions and sinks from composting yard trimmings 
and food discards (henceforth, organics). 1 It examines only emissions and sinks from centralized (e.g. 
municipal) composting, rather than from backyard composting or other localized composting operations. 
The chapter is organized as follows: 

Section 4.1 presents an estimate of potential anthropogenic GHG emissions from 

composting; 

Section 4.2 quantifies the potential carbon storage benefits of applying compost to soils; 

Section 4.3 presents net GHG emissions from composting; and 

Section 4.4 discusses the limitations of this analysis. 

Composting may result in (1) CH 4 emissions from anaerobic decomposition; (2) long-term carbon 
storage in the form of undecomposed carbon compounds; and (3) nonbiogenic C0 2 emissions from 
collection and transportation of the organic materials to the central composting site, and from mechanical 
turning of the compost pile. 2 Composting also results in biogenic C0 2 emissions associated with 
decomposition, both during the composting process and after the compost is added to the soil. Because 
this CO : is biogenic in origin, however, it is not counted as a GHG in the Inventory ofU.S. Greenhouse 
Gas Emissions and Sinks 3 (as explained in Section 1.4.2) and is not included in this accounting of 
emissions and sinks. 

Research suggests that composting, when managed properly, does not generate CH 4 emissions, 
but it does result in some carbon storage (associated with application of compost to soils), as well as 
minimal C0 2 emissions from transportation and mechanical turning of the compost piles. In order to 
maintain consistency with other chapters in this report, EPA selected point estimates from the range of 
emission factors—covering various compost application rates and time periods—developed in the 
analysis. The point estimates were chosen based on a “typical” compost application rate of 20 tons of 
compost per acre, averaged over three soil-crop scenarios. The carbon storage values for the year 2010 
were selected to be consistent with the time between onset of the program and carbon storage effect as 
simulated in the forest carbon storage estimates presented in Chapter 3 of this report. Overall, EPA 
estimates that centralized composting of organics results in net GHG storage of 0.05 MTCE/wet ton of 
organic inputs composted and applied to agricultural soil. 

4.1 POTENTIAL GHG EMISSIONS 

Two potential types of GHG emissions are associated with composting: (1) CH 4 from anaerobic 
decomposition, and (2) nonbiogenic C0 2 from transportation of compostable materials and turning of the 
compost piles. 


1 Although paper and mixed MSW can be composted, EPA did not analyze the GHG implications of composting 
them because of time and resource constraints. 

2 CO- emissions from delivery of compost to its final destination were not counted because compost is a marketable 
product, and C0 2 emissions from transportation of other marketable, finished goods to consumers have not been 
counted in other parts of this analysis. 

3 EPA. 2005. Inventory ofU.S. Greenhouse Gas Emissions and Sinks: 1990-2003. Environmental Protection 
Agency, Office of Policy! Planning and Evaluation, Washington, DC. EPA 430-R-05-003. 


49 





4.1.1 CH 4 

To research the issue of CH 4 emissions, EPA first conducted a literature search for articles on 
CH 4 generation from composting. Because CH 4 emissions from composting are addressed only 
occasionally in the literature, EPA contacted several composting experts from universities and USDA to 
discuss the potential for CH 4 generation, based on the nature of carbon flows during composting. The 
CH 4 analysis presented here is based on their expert opinions. 

The researchers EPA contacted stated that well-managed compost operations usually do not 
generate CH 4 because they typically maintain an aerobic environment with proper moisture content to 
encourage aerobic decomposition of the materials. The researchers also noted that even if CH 4 is 
generated in anaerobic pockets in the center of the compost pile, the CH 4 is most likely oxidized when it 
reaches the oxygen-rich surface of the pile, where it is converted to C0 2 . Several of the researchers 
commented that anaerobic pockets are most apt to develop when too much water is added to the compost 
pile. They noted that this problem rarely occurs because compost piles are much more likely to be 
watered too little rather than too much. 

EPA concluded from the available information that CH 4 generation from centralized compost 
piles is essentially zero. 

4.1.2 C0 2 from Transportation of Materials and Turning of Compost 

This study estimated the indirect C0 2 emissions associated with collecting and transporting 
organics to centralized compost facilities, and turning the compost piles. EPA began with estimates 
developed by FAL for the amount of diesel fuel required to (1) collect and transport 1 ton of organics 4 to 
a central composting facility (363,000 Btu) and (2) turn the compost pile (221,000 Btu). 5 EPA then 
converted these estimates to units of MTCE per ton of organics, based on a carbon coefficient of 0.02 
MTCE per million Btu of diesel fuel. This resulted in an estimate of 0.01 MTCE of indirect C0 2 
emissions per ton of material composted in a centralized facility. 

4.2 POTENTIAL CARBON STORAGE 

EPA also evaluated the effect of compost application on soil carbon storage. Information on 
carbon storage associated with compost derived specifically from yard trimmings or food discards was 
not found. Nevertheless, it is reasonable to expect that these materials have similar fates in terms of their 
stored carbon, even though their initial moisture and carbon contents differ. 

To develop carbon storage estimates for composted organics, EPA researched the processes that 
affect soil carbon storage, reviewed the results of experiments on the soil carbon impacts of applying 
organic amendments (e.g., compost, manure, biosolids, and crop residues), and interviewed experts on the 
potential carbon storage benefits of composting organics as compared to other methods of disposal. 
During this process, four hypotheses were proposed regarding the benefits of applying organics compost 
to soil: 

(1) Many soils have been depleted in organic matter through cultivation and other practices. Adding 
compost can raise soil carbon levels by increasing organic matter inputs. Soils degraded by 
intensive crop production, construction, mining, and other activities lose organic matter when 
decomposition rates and removals of carbon in harvests exceed the rate of new inputs of organic 
materials. Adding compost shifts the balance so that soil organic carbon levels are restored to 
higher levels. Some of the compost carbon is retained by the system. 


4 Measured on a wet weight basis, as MSW is typically measured. 

5 Franklin Associates, Ltd. 1994. The Role of Recycling in Integrated Solid Waste Management to the Year 2000 
(Stamford, CT: Keep America Beautiful), pp. 1-27, 30, and 31. 


50 



(2) Nitrogen in compost can stimulate higher productivity, thus generating more crop residues. This 
“fertilization effect” would increase soil carbon due to the larger volume of crop residues, which 
serve as organic matter inputs. 

(3) The composting process leads to increased formation of stable carbon compounds (e.g., humic 
substances, aggregates) that then can be stored in the soil for long (>50 years) periods of time. 
Humic substances make up 60-80 percent of soil organic matter and are made up of complex 
compounds that render them resistant to microbial attack. 6 7 In addition to humic substances, soil 
organic carbon may be held in aggregates (i.e., stable organo-mineral complexes in which carbon 
is bonded with clay colloids and metallic elements) and protected against microbial attack. 1 

(4) The application of compost produces a multiplier effect by qualitatively changing the dynamics 
of the carbon cycling system and increasing the retention of carbon from noncompost sources. 
Some studies of other compost feedstocks (e.g., farmyard manure, legumes) have indicated that 
the addition of organic matter to soil plots can increase the potential for storage of soil organic 
carbon. The carbon increase apparently comes not only from the organic matter directly, but also 
from retention of a higher proportion of carbon from residues of crops grown on the soil. This 
multiplier effect could enable compost to increase carbon storage by more than its own direct 
contribution to carbon mass accumulation. 

EPA’s research efforts did not yield any primary data that could be used to develop quantitative 
estimates of the soil carbon storage benefits of compost. Therefore, modeling approaches to investigate 
the possible effects of compost application on soil carbon storage were developed. Section 4.2.2 
describes application of the CENTURY model to quantify soil carbon restoration and nitrogen 
fertilization associated with compost application to carbon-depleted soils. EPA conducted a bounding 
analysis, described in Section 4.2.6, to address the third hypothesis, incremental humus formation. 
Although several of the experts contacted cited persuasive qualitative evidence of the existence of a 
multiplier effect, EPA was unable to develop an approach to quantify this process. In that sense, the 
carbon storage estimates are likely to be conservative (i.e., understate carbon storage rates), at least for 
soils with high silt and/or clay content where this process is most likely to apply. 

EPA’s analyses of soil carbon restoration, nitrogen fertilization, and incremental humus 
formation apply relatively simple models of very complex processes. These processes probably are 
controlled by a number of biological, physicochemical, and compost management factors, such as 
application (i.e., silviculture, horticulture, agriculture, and landscaping); application rate; regional and 
local climatic factors; soil type; and, to a lesser extent, compost feedstock (e.g., grass, leaves, branches, 
yard trimmings, food discards). In addition, the results are time-dependent, so the year in which benefits 
are assessed has an effect on the magnitude of carbon storage. 

Note that the framework used here describes the soil carbon benefits of composting relative to 
landfilling and combustion. In all three management methods, yard trimmings are collected and removed 
from soils in residential or commercial settings. This removal may result in some loss of organic carbon 
from the “home soil.” An estimate of the “absolute” soil carbon storage value would net out whatever 
loss occurs due to the removal of the yard trimmings. This effect is probably a negligible one, however, 
and EPA was unable to find empirical data on it. Because the decrement in carbon in “home soil” applies 
equally to all three management practices, and emission factors are intended to be viewed relative to other 
management practices (see Chapter 8), neglecting the carbon loss from the home soil does not 
compromise the validity of the results. 


6 N. Brady and R. Weil. 1999. The Nature and Properties of Soils (Upper Saddle River, NJ: Prentice Hall). 

7 R. Lai et al. 1998. The Potential ofU.S. Cropland to Sequester Carbon and Mitigate the Greenhouse Effect (Ann 
Arbor, MI: Sleeping Bear Press, Inc). 


51 



4.2.1 Modeling Soil Carbon Restoration and Nitrogen Fertilization 

As mentioned above, this analysis included an extensive literature review and interviews with 
experts to consider whether the'application of compost leads to long-term storage of carbon in soils. 

After determining that neither the literature review nor discussions with experts would yield a basis for a 
quantitative estimate of soil carbon storage, EPA evaluated the feasibility of a simulation modeling 
approach. EPA initially identified two simulation models with the potential to be applied to the issue ot 
soil carbon storage from compost application: CENTURY^ and the Rothamsted C (ROTHC-26.3) ? 
model. Both are peer-reviewed models whose structure and application have been described in scores of 
publications. They share several features: 

• Ability to run multiyear simulations; 

• Capability to construct multiple scenarios covering various climate and soil conditions and 
loading rates; and 

• Ability to handle interaction of several soil processes, environmental factors, and management 
scenarios such as carbon: nitrogen (C:N) ratios, aggregate formation, soil texture (e.g., clay 
content), and cropping regime. 

Given the extensive application of CENTURY in the United States, its availability on the Internet, and its 
ability to address many of the processes important to compost application, it was decided to use 
CENTURY rather than ROTHC-26.3. 

4.2.2 CENTURY Model Framework 

CENTURY is a Fortran model of plant-soil ecosystems that simulates long-term dynamics of 
carbon, nitrogen, phosphorus, and sulfur. It tracks the movement of carbon through soil pools—active, 
slow, and passive—and can show changes in carbon levels due to the addition of compost. 

In addition to soil organic matter pools, carbon can be found in surface (microbial) pools and in 
above- and below-ground litter pools. The above-ground and below-ground litter pools are divided into 
metabolic and structural pools based on the ratio of lignin to nitrogen in the litter. The structural pools 
contain all of the lignin and have much slower decay rates than the metabolic pools. Carbon additions to 
the system flow through the various pools and can exit the system (e.g., as CO 2 , dissolved carbon, or 
through crop removals). 

The above-ground and below-ground litter pools are split into metabolic and structural pools 
based on the ratio of lignin to nitrogen in the litter. The structural pools contain all of the lignin and have 
much slower decay rates than the metabolic pools. The active pool of soil organic matter includes living 
biomass, some of the fine particulate detritus, 10 most of the nonhumic material, and some of the more 
easily decomposed fulvic acids. The active pool is estimated to have a mean residence time (MRT) 11 of a 
few months to 10 years. 12 The slow pool includes resistant plant material (i.e., high lignin content) 
derived from the structural pool and other slowly decomposable and chemically resistant components. It 
has an MRT of 15-100 years. 1 ' The passive pool of soil organic matter includes very stable materials 
remaining in the soil for hundreds to thousands of years. 14 


* Metherell, A., L. Harding, C. Cole, W. Parton. 1993. CENTURY Agroecosystem Version 4.0, Great Plains 
System Research Unit Technical Report No. 4, USDA-ARS Global Climate Change Research Program (Colorado 
State University: Fort Collins, CO). 

0 This model was developed based on long-term observations of soil carbon at Rothamsted, an estate in the United 
Kingdom where organic amendments have been added to soils since the 19 th century. 

10 Detritus refers to debris from dead plants and animals. 

11 The term “mean residence time” is used interchangeably with “turnover time” and is the average time in which a 
unit (e.g., a carbon atom) resides within a “state” where there is both an input and an output. MRT is only strictly 
defined at steady-state (i.e., inputs = outputs), but as most soils systems have a continuing input of carbon and an 


52 



CENTURA does not simulate increased formation of humic substances associated with organic 
matter additions, nor does it allow for organic matter additions with high humus content to increase the 
magnitude of the passive pool directly. (Because CENTURY does not account for these processes, EPA 
developed a separate analysis, described in Section 4.2.6.) 

CENTURY contains a submodel to simulate soil organic matter pools. Additional submodels 
address nitrogen, phosphorus, sulfur, the water budget, leaching, soil temperature, and plant production, 
as well as individual submodels for various ecosystems (e.g., grassland, cropland). The nitrogen 
submodel addresses inputs ot fertilizer and other sources of nitrogen, mineralization of organic nitrogen, 
and uptake of nitrogen by plants. 

4.2.3 Inputs 

The CENTURY model simulates the long-term dynamics of various plant-soil ecosystems (e.g., 
grassland, agricultural land, forest, and savanna). The model uses a series of input files to specify 
modeling conditions: crop, harvest, fertilization, cultivation, organic matter addition, irrigation, grazing, 
fire, tree type, tree removal, site, and weather statistics. A schedule file is used to specify the timing of 
events. 


For this analysis, EPA developed a basic agricultural scenario where land was converted from 
prairie to farmland (growing com) in 1921 and remains growing com through 2030. More than 30 
scenarios were then run to examine the effect of several variables on soil carbon storage: 

• Compost application rate and frequency; 

• Site characteristics (rainfall, soil type, irrigation regime); 

• Fertilization rate; and 

• Crop residue management. 

Compost application rates were adjusted using the organic matter (compost) files for each 
compost application rate included in the analysis. EPA compared the effect of applying compost annually 
for 10 years (1996-2005) at seven different application rates: 1.3, 3.2, 6.5, 10, 15, 20, and 40 wet tons 
compost/acre (corresponding to 60-1,850 grams of carbon per square meter). 1 ' EPA also investigated the 
effect of compost application frequency on the soil carbon storage rate and total carbon levels. The model 
was run to simulate compost applications of 1.3 wet tons compost/acre and 3.2 wet tons compost/acre 
every year for 10 years (1996-2005) and applications of 1.3 wet tons compost/acre and 3.2 wet tons 
compost/acre applied every five years (in 1996, 2001, and 2006). The simulated 


approximately equal output through decomposition and transfer to other pools, MRT is often used to describe 
carbon dynamics in soils. Mathematically, it is the ratio of (a) mass in the pool to (b) throughput of carbon. For 
example, if a given carbon pool has a mass of 1,000 kg and the inflow is 1 kg/yr, the MRT is 1,000 kg / (1 kg/yr) = 

1,000 yr. 

12 Metherell et al. 1993, Brady and Weil 1999. 

13 Ibid. 

14 Ibid. 

15 The model requires inputs in terms of the carbon application rate in grams per square meter. The relationship 
between the carbon application rate and compost application rate depends on three factors: the moisture content of 
compost, the organic matter content (as a fraction of dry weight), and the carbon content (as a fraction of organic 
matter). Inputs are based on values provided by Dr. Harold Keener of Ohio State University, who estimates that 
compost has a moisture content of 50 percent, an organic matter fraction (as dry weight) ot 88 percent, and a carbon 
content of 48 percent (as a fraction of organic matter). Thus, on a wet weight basis, 21 percent ot compost is 
carbon. 


53 



compost was specified as having 33 percent lignin, 16 17:1 C:N ratio, 17 60:1 carbon-to-phosphorus ratio, 
and 75:1 carbon-to-sulfur ratio. Is EPA also ran a scenario with no compost application for each 
combination of site-fertilization-crop residue management. This scenario allowed EPA to control for 
compost application, i.e., to calculate the change in carbon storage attributable only to the addition ot 
compost. 

The majority of inputs needed to specify a scenario reside in the site file. The input variables in 
this file include the following: 

• Monthly average maximum and minimum air temperature; 

• Monthly precipitation; 

• Lignin content of plant material; 

• Plant nitrogen, phosphorus, and sulfur content; 

• Soil texture; 

• Atmospheric and soil nitrogen inputs; and 

• Initial soil carbon, nitrogen, phosphorus, and sulfur levels. 

Several sets of detailed site characteristics from past modeling applications are available to users. 
EPA chose two settings: an eastern Colorado site with clay loam soil and a southwestern Iowa site with 
silty clay loam soil. Both settings represent fairly typical Midwestern com belt situations where 
agricultural activities have depleted soil organic carbon levels. The Colorado scenario is available as a 
site file on the CENTURY Web site. 19 Dr. Keith Paustian, an expert in the development and application 
of CENTURY, provided the specifications for the Iowa site (as well as other input specifications and 
results for several of the runs described here). 

EPA also varied the fertilization rate. As discussed earlier, one of the hypotheses was that the 
mineralization of nitrogen in compost could stimulate crop growth, leading to production of more organic 
residues, which in turn would increase soil organic carbon levels. The strength of this effect would vary 
depending on the availability of other sources of nitrogen (N). To investigate this hypothesis, different 
rates of synthetic fertilizer addition ranging from zero up to a typical rate to attain average crop yield—90 
pounds (lbs.) N/acre for the Colorado site, 124 lbs. N/per acre for the Iowa site—were analyzed. EPA 
also evaluated fertilizer application at half of these typical rates. 

Finally, two harvest regimes were simulated, one where the com is harvested for silage (where 95 
percent of the above-ground biomass is removed) and the other where com is harvested for grain (where 
the “stover” is left behind to decompose on the field). These simulations enabled EPA to isolate the 


16 Percent lignin was estimated based on the lignin fractions for grass, leaves, and branches specified by compost 
experts (particularly Dr. Gregory Evanylo at Virginia Polytechnic Institute and State University, and lignin fractions 
reported in M.A. Barlaz, “Biodegradative Analysis of Municipal Solid Waste in Laboratory-Scale Landfills,” EPA 
600/R-97-071, 1997. FAL provided an estimate of the fraction of grass, leaves, and branches in yard trimmings in a 
personal communication with ICF Consulting, November 14, 1995. Subsequently, FAL obtained and provided data 
showing that the composition of yard trimmings varies widely in different states. The percentage composition used 
here (50 percent grass, 25 percent leaves, and 25 percent branches on a wet weight basis) is within the reported 
range. 

17 The C:N ratio was taken from Brady and Weil, 1999, The Nature and Property of Soils: Twelfth Edition (Upper 
Saddle River, NJ: Prentice Hall). 

C:P and C:S ratios were based on the literature and conversations with composting experts, including Dr. Gregory 
Evanylo at Virginia Polytechnic Institute and State University. 

19 The Natural Resource Ecology Laboratory at Colorado State University, CENTURY Soil Organic Matter Model, 
Version 5.0, available at: http://www.nrel.colostate.edu/proiects/centurv5 


54 





effect of the carbon added directly to the system in the form of compost, as opposed to total carbon inputs 
(which include crop residues). 

4.2.4 Outputs 

CENTURY is capable ot providing a variety of output data, including carbon storage in soils, 

C0 2 emissions due to microbial respiration, and monthly potential evapotranspiration. The outputs EPA 
chose were carbon levels for each of the eight soil pools: structural carbon in surface litter, metabolic 
carbon in surface litter, structural carbon in soil litter, metabolic carbon in soil litter, surface pool, active 
pool, slow pool, and passive pool. The output data cover the period from 1900 through 2030. In general, 
EPA focused on the difference in carbon storage between a baseline scenario, where no compost was 
applied, and a with-compost scenario. EPA calculated the difference between the two scenarios to isolate 
the effect of compost application. Output data in grams of carbon per square meter were converted to 
MTCE by multiplying by area (in square meters). 

To express results in units comparable to those for other sources and sinks, EPA divided the 
increase in carbon storage by the short tons of organics required to produce the compost. 20 That is, the 
factors are expressed as a carbon storage rate in units of MTCE per wet short ton of organic inputs (not 
MTCE per short ton of compost). 

4.2.5 Results 

The carbon storage rate declines with time after initial application. The rate is similar across application 
rates and frequencies, and across the site conditions that were simulated. Exhibit 4-1 displays results for 
the Colorado and Iowa sites, for the 10-, 20-, and 40-ton per acre application rates. As indicated on the 
graph, the soil carbon storage rate varies from about 0.08 MTCE per wet ton organics immediately after 
compost application (in 1997) to about 0.02 MTCE per ton in 2030 (24 years after the last application in 
2006). 

The similarity across the various site conditions and application rates reflects the fact that the 
dominant process controlling carbon retention is the decomposition of organic materials in the various 
pools. As simulated by CENTURY, this process is governed by first-order kinetics, i.e., the rate is 
independent of organic matter concentration or the rate of organic matter additions. 

Several secondary effects, however, result in some variation in the carbon storage rate. 21 EPA 
had hypothesized that where a crop’s demand for nitrogen exceeds its availability from other sources, 
mineralization of compost nitrogen can stimulate increased productivity. Simulation of this effect showed 
that where there is a shortage of nitrogen, compost application can result in higher productivity, which 
translates into higher inputs of crop residues to the soil. These higher inputs in turn increase the carbon 
storage rate per unit of compost inputs. This effect is a relatively modest one, however. 


20 EPA assumes 2.1 tons of yard trimmings are required to generate 1 ton of composted yard trimmings. Thus, to 
convert the results in this report (in MTCE per wet ton yard trimmings) to MTCE per wet ton of compost, multiply 
by 2.1. To convert to MTCE per dry ton compost, multiply values in this report by 4.2 (assuming 50 percent 
moisture content). 

21 In addition to the nitrogen fertilization effect, compost also affects moisture retention in soils, which in turn 
modifies the water balance relations simulated by CENTURY. 


55 



Exhibit 4-1 

Soil Carbon Storage-Colorado and Iowa sites; 10, 20, and 40 tons-per-acre Application Rates 



Year 



- CO 10 tpa 

• - - A- - 

- CO 20 tpa 


• CO 40 tpa 

-1— 

- 1A 10 tpa 

-*— 

- IA 20 tpa 


- IA 40 tpa 


Exhibit 4-2 shows the carbon storage rate for the Iowa site and the effect of nitrogen fertilization. 
The two curves in the exhibit both represent the difference in carbon storage between (a) a with-compost 
scenario (20 tons per acre) and (b) a baseline where compost is not applied. The nitrogen application 
rates differ in the following ways: 

• The curve labeled “Typical N application” represents application of 124 lbs. per acre, for both the 
compost and baseline scenario. Because the nitrogen added via compost has little effect when 
nitrogen is already in abundant supply, this curve portrays a situation where the carbon storage is 
attributable solely to the organic matter additions in the compost. 

• The curve labeled “Half N application” represents application of 62 lbs. per acre. In this 
scenario, mineralization of nitrogen added by the compost has an incremental effect on crop 
productivity compared to the baseline. The difference between the baseline and compost 
application runs reflects both organic matter added by the compost and additional biomass 
produced in response to the nitrogen contributed by the compost. 

The difference in incremental carbon storage rates between the two fertilization scenarios is less than 0.01 
MTCE per ton, indicating that the nitrogen fertilization effect is small. Note that this finding is based on 
the assumption that fanners applying compost also will apply sufficient synthetic fertilizer to maintain 
economic crop yields. If this assumption is not well-founded, or in situations where compost is applied as 
a soil amendment for road construction, landfill cover, or similar situations, the effect would be larger. 


56 





























Exhibit 4-2 Incremental Carbon Storage as a Function of Nitrogen Application Rate 



Year 


When viewed from the perspective of total carbon, rather than as a storage rate per ton of inputs 
to the composting process, both soil organic carbon concentrations and total carbon stored per acre 
increase with increasing application rates (see Exhibit 4-3). Soil organic carbon concentrations increase 
throughout the period of compost application, peak in 2006 (the last year of application), and decline 
thereafter due to decomposition of the imported carbon. Exhibit 4-3 displays total carbon storage 
(including baseline carbon) in soils on the order of 40 to 65 metric tons per acre (the range would be 
higher with higher compost application rates or longer term applications). 

4.2.6 Incremental Humus Formation 

The third of the four hypotheses describing the benefits of composting, as compared to alternative 
management methods, is predicated on incremental formation of stable carbon compounds that can be 
stored in the soil for long periods of time. CENTURY does not simulate this process, i.e., it does not 
allow for organic matter additions with high humus content to directly increase the magnitude of the 
passive pool. Therefore, EPA used a bounding analysis to estimate the upper and lower limits of the 
magnitude of this effect. In this analysis, EPA evaluated the amount of long-term soil carbon storage 
when organics are composted and applied to soil. 

During the process of decomposition, organic materials typically go through a series of steps 
before finally being converted to C0 2 , water, and other reaction products. The intermediate compounds 
that are formed, and the lifetime of these compounds, can vary widely depending on a number of factors, 
including the chemical composition of the parent compound. Parent compounds range from readily 
degradable molecules such as cellulose and hemicellulose to molecules more resistant to degradation, 
such as lignin, waxes, and tannins. 


57 

















Exhibit 4-3 Total Soil C; Iowa Site, Corn Harvested for Grain 



Year 


0) 

1 _ 

o 


< 


V) 

c 

o 

I- 

o 


o 


— •— Baseline 
—K— 1.3 tons/acre 
— A — 20 tons/acre 


Composting is designed to promote rapid decomposition of organics, thus reducing their volume. 
Some evidence suggests that composting produces a greater proportion of humus than that typically 
formed when organics are left directly on the ground. The conditions in the two phases are different. The 
heat generated within compost piles favors “thermophilic” (heat-loving) bacteria, which tend to produce a 
greater proportion of stable, long-chain carbon compounds (e.g., humic substances) than do bacteria and 
fungi that predominate at ambient soil temperatures. 

Increased humus formation associated with compost application is a function of two principal 

factors: 

(1) The fraction of carbon in compost that is considered “passive” (i.e., very stable); and 

(2) The rate at which passive carbon is degraded to C0 2 . 

Estimates for the first factor are based on experimental data compiled by Dr. Michael Cole of the 
University of Illinois. Dr. Cole found literature values indicating that between 4 and 20 percent of the 
carbon in finished compost degrades quickly. 22 Dr. Cole averaged the values he found in the literature 
and estimated that 10 percent of the carbon in compost can be considered “fast” (i.e., readily degradable). 
The remaining 90 percent can be classified as either slow or passive. EPA was unable to locate 
experimental data that delineate the fractions of slow and passive carbon in compost; therefore, upper and 
lower bound estimates based on Dr. Cole’s professional judgment were developed. He suggested values 

22 Very little information is available on the characteristics of compost derived from yard trimmings or food 
discards. However, Dr. Cole found that the composition of composts derived from other materials is broadly 
consistent, suggesting that his estimates may be reasonably applied to yard trimmings or food scrap compost. 


58 



























of 30 percent slow and 60 percent passive, and 45 percent slow and 45 percent passive for the upper and 
lower bounds on passive content, respectively. 23 

For the second factor, EPA chose a mean residence time for passive carbon of 400 years based on 
the range of values specified in the literature. 24 

Combining the two bounds for incremental humus formation (60 percent passive and 45 percent 
passive), EPA estimated the incremental carbon storage implied by each scenario (see Exhibit 4-4). 

The upper bound on the incremental carbon storage from composting is more than 0.05 MTCE 
per wet ton of organics (shown in the top left of the graph); the lower bound is approximately 0.03 MTCE 
per wet ton (shown in the bottom right of the graph) after about 100 years. Incremental storage is 
sensitive to the fraction of carbon in compost that is passive but is not very sensitive to the degradation 
rate (within a 100-year time horizon, over the range of rate constants appropriate for passive carbon). 

To select a point estimate for the effect of incremental humus fonnation, EPA took the average 
storage value across the two bounding scenarios, when time equals 10 years (i.e., approximately 2010). 
The resulting value is 0.046 MTCE/ton. The 2010 time frame was chosen for this analysis because the 
forest carbon estimates presented in Chapter 3 of this report are for the period ending in 2010. 


Exhibit 4-4 Incremental Carbon Storage: MTCE/Wet Ton Versus Time 



23 EPA focused only on the passive pool because (1) the CENTURY model does not allow for direct input of 
organic carbon into the passive pool, and (2) the model runs resulted in very little indirect (i.e., via other pools) 
formation of passive carbon. Although the first factor is also true toi the slow' pool, the second is not. Had EPA 
analyzed slow carbon in the same way as passive carbon, there would be potential foi double counting (see 

discussion in Section 4.3). 

24 Metherell et al. 1993, Brady and Weil 1999. 


59 










4.3 NET GHG EMISSIONS FROM COMPOSTING 


The approaches described in Section 4.2 were adopted to capture the range of carbon storage 
benefits associated with compost application. However, this dual approach creates the possibility of 
double counting. In an effort to eliminate double counting, EPA evaluated the way that CENTURY 
partitions compost carbon once it is applied to the soil. 

To do so, EPA ran a CENTURY model simulation of compost addition during a single year and 
compared the results to a corresponding reference case (without compost). EPA calculated the difference 
in carbon in each of the CENTURY pools for the two simulations and found that the change in the 
passive pool represented less than 0.01 percent of the change in total carbon. Therefore, CENTURY is 
not adding recalcitrant carbon directly to the passive pool. Next, EPA graphed the change in the passive 
pool over time to ensure that the recalcitrant compost carbon was not being cycled from the faster pools 
into the passive pool several years after the compost is applied. As Exhibit 4-5 shows, CENTURY does 
not introduce significant increments (over the base case) of recalcitrant carbon into the passive pool at any 
time. 

Exhibit 4-5 Difference in Carbon Storage Between Compost Addition and Base Case Yearly 

Application with 20 Tons Compost 



1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 2020 2023 2026 2029 


—-x— Passive 
-Total Carbon 


Year 


Based on the analysis, it appears that CENTURY is appropriately simulating carbon cycling and 
storage tor all but the passive carbon introduced by compost application. Because passive carbon 
represents approximately 52 percent of carbon in compost (the midpoint of 45 percent and 60 percent), 
EPA scaled the CENTURY results by 48 percent to reflect the proportion of carbon that can be classified 

as fast or slow (i.e., not passive). 


60 














Exhibit 4-6 shows the soil carbon storage and transportation-related emissions and sinks, and 
sums these to derive estimates of a net GHG emission factor, using the same sign convention as the 
broader analysis. A negative value denotes carbon storage; a positive value denotes emissions. 

Summing the values corresponding to typical application rate and the 2010 time frame for soil 
carbon restoration (-0.02 MTCE/ton), increased humus formation (-0.05 MTCE/ton), and transportation 
emissions (0.01 MTCE/ton), the result is -0.05 MTCE/ton. 2 '' 

Exhibit 4-6 


Net GHG Emissions from Composting 
(In MTCE Per Ton of Yard Trimmings Composted) 


Emission/ Storage Factor (for 2010) 

Soil Carbon Restoration 

Increased 

Humus 

Formation 

Transportation 

Emissions 

Net Carbon 
Flux 

Unweighted 

Proportion of 

C that is Not 
Passive 

Weighted 

Estimate 

-0.04 

48% 

-0.02 

-0.05 

0.01 

-0.05 


4.4 LIMITATIONS 

Due to data and resource constraints, this chapter does not explore the full range of conditions 
under which compost is managed and applied, and how these conditions would affect the results of this 
analysis. Instead, this study attempts to provide an analysis of GHG emissions and sinks associated with 
centralized composting of organics under a limited set of scenarios. EPA’s analysis was limited by the 
lack of primary research on carbon storage and CH 4 generation associated with composting. The limited 
availability of data forced EPA to rely on two modeling approaches, each with its own set of limitations. 
In addition, the analysis was limited by the scope of the report, which is intended to present life-cycle 
GHG emissions of waste management practices for selected material types, including food discards and 
yard trimmings. 

4.4.1 Limitations of Modeling Approaches 

Due to data and resource constraints, EPA was unable to use CENTURY to evaluate the variation 
in carbon storage impacts for a wide range of compost feedstocks (e.g., yard trimmings mixed with food 
discards, food discards alone). As noted earlier, resource constraints limited the number of soil types, 
climates, and compost applications simulated. The CENTURY results also incorporate the limitations of 
the model itself, which have been well documented elsewhere. Perhaps most importantly, the model’s 
predictions of soil organic matter levels are driven by four variables: annual precipitation, temperature, 
soil texture, and plant lignin content. Beyond these, the model is limited by its sensitivity to several 
factors for which data are difficult or impossible to obtain (e.g., presettlement grazing intensity, nitrogen 
input during soil development). 26 The model’s monthly simulation intervals limit its ability to fully 
address potential interactions between nitrogen supply, plant growth, soil moisture, and decomposition 
rates, which may be sensitive to conditions that vary on a shorter time scale. 27 In addition, the model is 
not designed to capture the hypothesis that, due to compost application, soil ecosystem dynamics change 
so that more carbon is stored than is actually being added to the soil (i.e., the multiplier ettect). 


25 The addends do not sum to the total, due to rounding. 

26 Parton, W., D. Schimel, C. Cole, and D. Ojirna. 1987. “Analysis of Factors Controlling Soil Organic Matter 
Levels in Great Plains Grasslands.” Soil Sci. Soc. Am. J. Vol. 51 (1173-1 179). 

27 Paustian, K., W. Parton, and Jan Persson. 1992. “Modeling Soil Organic Matter in Organic-Amended and 
Nitrogen-Fertilized Long-Term Plots.’ Soil Sci. Soc. Am. J. V ol. 56 (476-488). 


61 












CENTURY simulates carbon movement through organic matter pools. Although the model is 
designed to evaluate additions of organic matter in general, it is not believed to have been applied in the 
past to evaluate the application of organics compost. CENTURY is parameterized to partition carbon to 
the various pools based on ratios of lignin to nitrogen and lignin to total carbon, not on the amount ot 
organic material that has been converted to humus already. EPA addressed this limitation by developing 
an “add-on” analysis to evaluate humus formation in the passive pool, scaling the CENTURY results, and 
summing the soil carbon storage values. There is some potential for double counting, to the extent that 
CENTURY is routing some carbon to various pools that is also accounted for in the incremental humus 
analysis. EPA believes that this effect is likely to be minor. 

The bounding analysis used to analyze increased humus formation is limited by the lack of data 
specifically dealing with composts composed of yard trimmings or food discards. This analysis is also 
limited by the lack of data on carbon in compost that is passive. The approach of taking the average value 
from the two scenarios is simplistic but appears to be the best available option. 

4.4.2 Limitations Related to the Scope of the Report 

As indicated above, this chapter presents EPA’s estimates of the GHG-related impacts of 
composting organics. These estimates were developed within the framework of the larger report; 
therefore, the presentation of results, estimation of emissions and sinks, and description of ancillary 
benefits is not comprehensive. The remainder of this section describes specific limitations of the compost 
analysis. 

As in the other chapters of this report, the GHG impacts of composting reported in this chapter 
are relative to other possible disposal options for yard trimmings (i.e., landfilling and combustion). In 
order to present absolute GHG emission factors for composted yard trimmings that could be used to 
compare composting to a baseline of leaving yard trimmings on the ground where they fall, EPA would 
need to analyze the home soil. In particular, the carbon storage benefits of composting would need to be 
compared to the impact of removal of yard trimmings on the home soil. 

As mentioned in Section 4.4.1, due to data and resource constraints, the analysis considers a small 
sampling of feedstocks and a single compost application (i.e., agricultural soil). EPA analyzed two types 
of compost feedstocks—yard trimmings and food discards—although sewage sludge, animal manure, and 
several other compost feedstocks also may have significant GHG implications. Similarly, it was assumed 
that compost was applied to degraded agricultural soils, despite widespread use of compost in land 
reclamation, silviculture, horticulture, and landscaping. 

This analysis did not consider the full range of soil conservation and management practices that 
could be used in combination with compost and the impacts of those practices on carbon storage. Some 
research indicates that adding compost to agricultural soils in conjunction with various conservation 
practices enhances the generation of soil organic matter to a much greater degree than applying compost 
alone. Examples of these conservation practices include conservation tillage, no tillage, residue 
management, crop rotation, wintering, and summer fallow elimination. Research suggests that allowing 
crop residues to remain on the soil rather than turning them over helps to protect and sustain the soil while 
simultaneously enriching it. Alternatively, conventional tillage techniques accelerate soil erosion, 
increase soil aeration, and hence lead to greater GHG emissions. 28 Compost use also has been shown to 
increase soil water retention; moister soil gives a number of ancillary benefits, including reduced 
irrigation costs and reduced energy used for pumping water. Compost can also play an important role in 
the adaptation strategies that will be necessary as climate zones shift with climate change and some areas 
become more arid. 


R. Lai et al. 1998. The Potential ofU.S. Cropland to Sequester Carbon and Mitigate the Greenhouse Effect (Ann 
Arbor, MI: Sleeping Bear Press, Inc). 


62 



As is the case in other chapters, the methodology used to estimate GHG emissions from 
composting did not allow for variations in transportation distances. EPA recognizes that the density of 
landfills versus composting sites in any given area would have an effect on the extent of transportation 
emissions derived from composting. For example, in states that have a higher density of composting 
sites, the hauling distance to such a site would be less and would require less fuel than transportation to a 
landfill. Alternatively, transporting compost from urban areas, where compost feedstocks may be 
collected, to farmlands, where compost is typically applied, potentially would require more fuel because 
of the large distance separating the sites. 

Emission factors presented in this chapter do not capture the full range of possible GE1G 
emissions from compost. Some of the nitrogen in compost is volatilized and released into the atmosphere 
as N 2 0 shortly after application of the compost. Based on a screening analysis, N 2 0 emissions were 
estimated to be less than 0.01 MTCE per wet ton of compost inputs. 

Addressing the possible GHG emission reductions and other environmental benefits achievable 
by applying compost instead of chemical fertilizers, fungicides, and pesticides was beyond the scope of 
this report. Manufacturing those agricultural products requires energy. To the extent that compost may 
replace or reduce the need for these substances, composting may result in reduced energy-related GHG 
emissions. Although EPA understands that compost is generally applied for its soil amendment 
properties rather than for pest control, compost has been effective in reducing the need for harmful or 
toxic pesticides and fungicides. 20 

In addition to the carbon storage benefits of adding compost to agricultural soils, composting can 
lead to improved soil quality, improved productivity, and cost savings. As discussed earlier, nutrients in 
compost tend to foster soil fertility. 30 In fact, composts have been used to establish plant growth on land 
previously unable to support vegetation. In addition to these biological improvements, compost also may 
lead to cost savings associated with avoided waste disposal, particularly for feedstocks such as sewage 
sludge and animal manure. 


29 For example, the use of compost may reduce or eliminate the need for soil fumigation with methyl bromide (an 
ozone-depleting substance) to kill plant pests and pathogens. 

30 N. Brady and R. Weil. 1999. 


63 



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64 


5. COMBUSTION 


This chapter presents estimates of the net GHG emissions from combustion of most of the 
materials considered in this analysis and several categories of mixed waste streams (e.g., mixed paper, 
mixed recyclables, and mixed MSW). Combustion of MSW results in emissions of CO 2 (because nearly 
all of the carbon in MSW is converted to C0 2 under optimal conditions) and N 2 0. Note that C0 2 from 
burning biomass sources (such as paper products and yard trimmings) is not counted as a GHG because it 
is biogenic (as explained in Section 1.4.2). 

Combustion of MSW with energy recovery in a waste-to-energy (WTE) plant also results in 
avoided C0 2 emissions at utility and metals production facilities. First, the electricity produced by a 
WTE plant displaces electricity that would otherwise be provided by an electric utility power plant. 
Because most utility power plants bum fossil fuels and thus emit C0 2 , the electricity produced by a WTE 
plant reduces utility C0 2 emissions. These avoided GHG emissions are subtracted from the GHG 
emissions associated with combustion of MSW. Second, most MSW combusted with energy recovery in 
the United States is combusted in WTE plants that recover ferrous metals (e.g., steel) and nonferrous 
materials (e.g., nonferrous metals and glass). 1 The recovered ferrous metals and nonferrous materials 
then are recycled. As discussed in Chapter 4, processes using recycled inputs require less energy than 
processes using virgin inputs. In measuring GHG implications of combustion, one also must account for 
the change in energy use due to recycling associated with metals recovery. 

WTE facilities can be divided into three categories: (1) mass burn, (2) modular, or (3) refuse- 
derived fuel (RDF). A mass bum facility generates electricity and/or steam from the combustion of 
mixed MSW. In the United States, about 65 mass bum facilities process approximately 22 million tons of 
MSW annually. 2 3 Modular WTE plants generally are smaller than mass bum plants and are prefabricated 
off-site so that they can be assembled quickly where they are needed. Because of their similarity to mass 
bum facilities, modular facilities are treated as part of the mass bum category for the purposes of this 
analysis. 

An RDF facility combusts MSW that has undergone varying degrees of processing, from simple 
removal of bulky and noncombustible items to more complex processes (shredding and material 
recovery) that result in a finely divided fuel. Processing MSW into RDF yields a more uniform fuel that 
has a higher heating value than is produced by mass bum or modular WTE.' In the United States, 
approximately 10 facilities process and combust RDF, 5 facilities combust RDF using off-site processing, 
and 5 facilities process RDF for combustion off-site. These RDF facilities process approximately 8 
million tons of MSW annually. 4 

This study analyzed the net GHG emissions from combustion of mixed waste streams and the 
following individual materials at mass bum and RDF facilities: 


1 EPA did not consider any recovery of materials from the MSW stream that may occur before MSW is delivered to 
the combustor. EPA considered such prior recovery to be unrelated to the combustion operation—unlike recovery 
of steel from combustor ash, an activity that is an integral part of the operation of many combustors. 

2 Integrated Waste Services Association, The 2004IWSA Waste-To-Energy Directory of United States Facilities , 

Table 1. 

3 MSW processing into RDF involves both manual and mechanical separation to remove materials such as glass and 
metals that have little or no fuel value. 

4 Integrated Waste Services Association, The 2004 IWSA Waste-To-Energy> Directory of United States Facilities , 
Table 1. 


65 






• Aluminum Cans; 

• Steel Cans; 

• Copper Wire; 

• Glass; 

• HDPE Plastic; 

• LDPE Plastic; 

• PET Plastic; 

• Corrugated Cardboard; 

• Magazines and Third-class Mail; 

• Newspaper; 

• Office Paper; 

• Phonebooks;" 

• Textbooks; 6 

• Dimensional Lumber; 

• Medium-density Fiberboard; 

• Food Discards; 

• Yard Trimmings; 

• Carpet; 

• Personal Computers; and 

• Tires. 

Net emissions consist of (1) emissions of nonbiogenic C0 2 and N 2 0 minus (2) avoided GHG 
emissions from the electric utility sector and from processing with recycled inputs (e.g., steel produced 
from recycled inputs requires less energy than steel from virgin inputs). There is some evidence that as 
combustor ash ages, it absorbs C0 2 from the atmosphere. However, EP A did not count absorbed C0 2 
because the quantity is estimated to be less than 0.01 MTCE per ton of MSW combusted. Similarly, the 
residual waste from processing MSW into RDF is typically landfilled. Some potential exists for the 
organic fraction of this residual waste to yield GHG emissions when landfilled. EPA did not count these 
emissions, however, because the quantity emitted is estimated to be less than 0.01 MTCE per ton of MSW 
processed into RDF. S 6 7 8 

The results showed that combustion of mixed MSW has small negative net GHG emissions (in 
absolute terms). Combustion of paper products, dimensional lumber, medium-density fiberboard, food 


5 Newspaper used as proxy, as material-specific data were unavailable. 

6 Office paper used as proxy, as material-specific data were unavailable. 

7 Based on data provided by Dr. Jurgen Vehlow, of the Institut fur Technische Chemie in Karlsruhe, Gennany, EPA 
estimated that the ash from 1 ton of MSW would absorb roughly 0.004 MTCE of C0 2 . 

8 Based on data provided by Karen Harrington, principal planner for the Minnesota Office of Environmental 
Assistance, EPA estimated that landfilling the residual waste would emit roughly 0.003 MTCE of C0 2 per ton of 
MSW processed into RDF. Facsimile from Karen Harrington, Minnesota Office of Environmental Assistance to 
ICF Consulting, October 1997. 


66 




discards, yard trimmings, and personal computers results in negative net GHG emissions. Processing 
steel cans at a combustor, followed by recycling the ferrous metal, likewise results in negative net GHG 
emissions. Combustion ot plastic produces positive net GHG emissions, and combustion of aluminum 
cans, copper wire, and glass results in small positive net GHG emissions. The reasons for each of these 
results are discussed in this chapter. 9 

5.1 METHODOLOGY 

The study’s general approach was to estimate the (1) gross emissions of C0 2 and N 2 0 from MSW 
and RDF combustion (including emissions from transportation of waste to the combustor and ash from 
the combustor to a landfill) and (2) C0 2 emissions avoided due to displaced electric utility generation and 
decreased energy requirements for production processes using recycled inputs. 10 To obtain an estimate of 
the net GHG emissions from MSW and RDF combustion, the GHG emissions avoided was subtracted 
from the direct GHG emissions. EPA estimated the net GHG emissions from waste combustion per ton of 
mixed MSW and per ton of each selected material in MSW. The remainder of this section describes how 
EPA developed these estimates. 

5.1.1 Estimating Direct C0 2 Emissions from MSW Combustion 

The carbon in MSW has two distinct origins. Some of it is derived from sustainably harvested 
biomass (i.e., carbon in plant and animal matter that was converted from C0 2 in the atmosphere through 
photosynthesis). The remaining carbon in MSW is from nonbiomass sources, e.g., plastic and synthetic 
rubber derived from petroleum. 

For reasons described in Section 1.4.2, EPA did not count the biogenic C0 2 emissions from 
combustion of biomass. On the other hand, C0 2 emissions from combustion of nonbiomass components 
of MSW—plastic, textiles, and rubber—were counted. Overall, only a small portion of the total C0 2 
emissions from combustion are counted as GHG emissions. 

For mixed MSW, EPA used the simplifying assumptions that (1) all carbon in textiles is 
nonbiomass carbon, i.e., petrochemical-based plastic fibers such as polyester (this is a worst-case 
assumption); and (2) the category of “rubber and leather” in EPA’s MSW characterization report * 11 is 
composed almost entirely of rubber. Based on these assumptions, EPA estimated that there are 0.11 lbs. 
of nonbiogenic carbon in the plastic, textiles, rubber, and leather contained in one lb. of mixed MSW. 12 
EPA assumed that 98 percent of this carbon would be converted to C0 2 when the waste is combusted, 
with the balance going to the ash. The 0.11 lbs. of nonbiomass carbon per one lb. of mixed MSW then 
was converted to units of MTCE per ton of mixed MSW combusted. The resulting value for mixed MSW 
is 0.10 MTCE per ton of mixed MSW combusted, 12 as shown in Exhibit 5-1. 


9 Note that Exhibit 5-1, Exhibit 5-2, and Exhibit 5-5 do not show mixed paper. Mixed paper is shown in the 
summary exhibit (Exhibit 5-6). The summary values for mixed paper are based on the proportions of the four paper 
types (newspaper, office paper, corrugated cardboard, and magazines/third-class mail) that make up the different 
“mixed paper” definitions. 

10 A comprehensive evaluation also would consider the fate of carbon remaining in combustor ash. Depending on 
its chemical form, carbon may be aerobically degraded to C0 2 , anaerobically degraded to CH 4 , or remain in a 
relatively inert form and be stored. Unless the ash carbon is converted to CH 4 (which EPA considers unlikely), the 
effect on the net GHG emissions would be very small. 

11 EPA 2005. Municipal Solid Waste in the United States: 2003 Facts and Figures. Office of Solid Waste. 
EPA530-F-05-003. 

12 ICF Consulting. 1995. Memorandum. “Work Assignment 239, Task 2: Carbon Sequestration in Landfills,” April 
28, Exhibit 2-A, column “o.” 

13 Note that if EPA had used a best-case assumption for textiles, i.e., assuming they have no petrochemical-based 
fibers, the resulting value for mixed MSW would have been 0.09 MTCE per ton ot mixed MSW combusted. 


67 



EPA estimated that HDPE and LDPE are 84 percent carbon, while PET is 57 percent carbon 
(based on a moisture content of 2 percent). EPA assumed that 98 percent of the carbon in the plastic is 
converted to C0 2 during combustion. The values for C0 2 emissions, converted to units of MTCE per ton 
of plastic combusted, are shown in column “b” of Exhibit 5-1. 

5.1.2 Estimating N 2 0 Emissions from Combustion of Waste 

Studies compiled by the IPCC show that MSW combustion results in measurable emissions of 
N 2 0, a GHG with a high GWP. 14 The IPCC compiled reported ranges of N 2 0 emissions, per metric ton 
of waste combusted, from six classifications of MSW combustors. This study averaged the midpoints of 
each range and converted the units to MTCE of N 2 0 per ton of MSW. The resulting estimate is 0.01 
MTCE of N 2 0 emissions per ton of mixed MSW combusted. Because the IPCC did not report N 2 0 
values for combustion of individual components of MSW, EPA used the 0.01 value not only for mixed 
MSW, but also as a proxy for all components of MSW, except for aluminum cans, steel cans, glass, 

HDPE, LDPE, and PET. 15 

5.1.3 Estimating Indirect C0 2 Emissions from Transportation of Waste to the Facility 

Next, this study estimated the indirect C0 2 emissions from the transportation of waste. For the 
indirect C0 2 emissions from transporting waste to the combustion facility, and ash from the combustion 
facility to a landfill, EPA used an estimate for mixed MSW developed by FAL. 16 EPA then converted the 
FAL estimate from pounds of C0 2 per ton of mixed MSW to MTCE per ton of mixed MSW. This 
resulted in an estimate of 0.01 MTCE of C0 2 emissions from transporting 1 ton of mixed MSW and the 
resulting ash. Transportation of any individual material in MSW was assumed to use the same amount of 
energy as transportation of mixed MSW. 

5.1.4 Estimating Gross GHG Emissions from Combustion 

To estimate the gross GHG emissions per ton of waste combusted, EPA summed the values for 
emissions from combustion C0 2 , combustion N 2 0, and transportation C0 2 . The gross GHG emission 
estimates, for mixed MSW and for each individual material, are shown in column “e” of Exhibit 5-1. 

5.1.5 Estimating Utility C0 2 Emissions Avoided 

Most WTE plants in the United States produce electricity. Only a few cogenerate electricity and 
steam. In this analysis, EPA assumed that the energy recovered with MSW combustion would be in the 
form of electricity. This analysis is shown in Exhibit 5-2. EPA used three data elements to estimate the 
avoided electric utility C0 2 emissions associated with combustion of waste in a WTE plant: (1) the 
energy content of mixed MSW and of each separate waste material considered, (2) the combustion system 
efficiency in converting energy in MSW to delivered electricity, and (3) the electric utility C0 2 emissions 
avoided per kilowatt-hour (kWh) of electricity delivered by WTE plants. 

Energy content: For the energy content of mixed MSW, EPA used a value of 5,000 Btu per 
pound of mixed MSW combusted, which is a value commonly used in the WTE industry. 17 This estimate 


14 U.S. EPA, 2006, Inventory ofU.S. Greenhouse Gas Emissions and Sinks: 1990-2004, available online at: 
http://vosemite.epa.gov/oar/globalwanning.nsf/content/ResourceCenterPublicationsGHGEmissions.html . The 

GWP of N 2 0 is 310 times that of C0 2 . 

15 This exception was made because at the relatively low combustion temperatures found in MSW combustors, most 
of the nitrogen in N 2 0 emissions is derived from the waste, not from the combustion air. Because aluminum and 
steel cans, glass, and plastics do not contain nitrogen, EPA concluded that running these materials through an MSW 
combustor would not result in N 2 0 emissions. 

16 FAL. 1994. The Role of Recycling in Integrated Solid Waste Management to the Year 2000 (Stamford, CT: Keep 
America Beautiful, Inc.), p. 1-24. 

17 Telephone conversation among representatives of Integrated Waste Services Association, American Ref-Fuel, and 
ICF Consulting, October 28, 1997. 


68 





is within the range of values (4,500 to 6,500 Btu per pound) reported by FAL 18 and is slightly higher than 
the 4,800 Btu per pound value reported in EPA’s MSWFact Book . |g For the energy content of RDF, a 
value ot 5,700 Btu per pound of RDF combusted was used. 20 This estimate is within the range of values 
(4,800 to 6,400 Btu per pound) reported by the DOE’s National Renewable Energy Laboratory (NREL). 21 
For the energy content of specific materials in MSW, EPA consulted three sources: (1) EPA’s MSW Fact 
Book (a compilation of data from primary sources), (2) a report by Environment Canada, 22 and (3) a 
report by Argonne National Laboratories. 23 EPA assumes that the energy contents reported in the first 
two of these sources were for materials with moisture contents typically found for the materials in MSW 
(the sources implied this but did not explicitly state it). The Argonne study reported energy content on a 
dry weight basis. 

Combustion system efficiency: To estimate the combustion system efficiency of mass bum 
plants, EPA used a net value of 550 kWh generated by mass bum plants per ton of mixed MSW 
combusted. 24 

To estimate the combustion system efficiency of RDF plants, EPA evaluated three sources: (1) data 
supplied by an RDF processing facility located in Newport, MN; (2) the Integrated Waste Services 
Association (IWSA) report Waste-to-Energy Directory: Year 2000 ; and (3) the DOE NREL. EPA used 
the Newport Processing Facility’s reported net value of 572 kWh generated per ton of RDF for two 
reasons. 2 ' First, this value is within the range of values reported by the other sources. Second, the 
Newport Processing Facility provided a complete set of data for evaluating the overall system efficiency 
of RDF plants. 26 


18 FAL. 1994. The Role of Recycling in Integrated Solid Waste Management to the Year 2000 (Stamford, CT: Keep 
America Beautiful, Inc.), pp. 1-16. 

19 EPA, Office of Solid Waste. 1995. MSW Fact Book, Version 2.0 (Washington, D.C.: U.S. Environmental 
Protection Agency). 

20 Note that this is a value reported by an RDF facility located in Newport, MN; the data were provided by the 
Minnesota Office of Environmental Assistance. Facsimile from Karen Harrington, Minnesota Office of 
Environmental Assistance to ICF Consulting, October 1997. 

21 DOE, National Renewable Energy Laboratory. 1992. Data Summary of Municipal Solid Waste Management 
Alternatives Volume IV: Appendix B - RDF Technologies (Springfield, VA: National Technical Information Service, 
NREL/TP-431-4988D), p. B-5. 

22 Procter and Redfem, Ltd. and ORTECH International. 1993. Estimation of the Effects of Various Municipal 
Waste Management Strategies on Greenhouse Gas Emissions, Part II (Ottawa, Canada: Environment Canada, Solid 
Waste Management Division, and Natural Resources Canada, Alternative Energy Division). 

23 Gaines, Linda, and Frank Stodolsky. 1993. Mandated Recycling Rates: Impacts on Energy Consumption and 
Municipal Solid Waste Volume (Argonne, IL: Argonne National Laboratory), pp. 11 and 85. 

24 Note that this is the value reported by Integrated Waste Services Association in its comments to the draft version 
of the first edition of this report. This value is within the range of values reported by others in response to the draft. 
Letter received from Maria Zannes, Integrated Waste Services Association, Washington, DC, August 25, 1997. 

25 The net energy value reported accounts for the estimated energy required to process MSW into RDF and the 
estimated energy consumed by the RDF combustion facility. 

26 The dataset included estimates on the composition and amount of MSW delivered to the processing facility, as 
well as estimates for the heat value of RDF, the amount of energy required to process MSW into RDF, and the 
amount of energy used to operate the RDF facility. 


69 




Exhibit 5-1 

Gross Emissions of GHGs from MSW Co mbustion (MTCE per Ton Combusted) 


(a) 

Material Combusted 

(b) 

Combustion 
C0 2 Emissions 
From 

Nonbiomass 

(c) 

Combustion 

n 2 o 

Emissions 

(d) 

Transportation 
C0 2 Emissions 

(e) 

(e = b + c + d) 
Gross GHG 
Emissions 

Aluminum Cans 

0.00 

0.00 

0.01 

0.01 

Steel Cans 

0.00 

0.00 

0.01 

0.01 

Copper Wire 

0.00 

0.00 

0.01 

0.01 

Glass 

0.00 

0.00 

0.01 

0.01 

HDPE 

0.76 

0.00 

0.01 

0.77 

LDPE 

0.76 

0.00 

0.01 

0.77 

PET 

0.56 

0.00 

0.01 

0.56 

Corrugated Cardboard 

0.00 

0.01 

0.01 

0.02 

Magazines/Third-class Mail 

0.00 

0.01 

0.01 

0.02 

Newspaper 

0.00 

0.01 

0.01 

0.02 

Office Paper 

0.00 

0.01 

0.01 

0.02 

Phonebooks 3 

0.00 

0.01 

0.01 

0.02 

Textbooks 3 

0.00 

0.01 

0.01 

0.02 

Dimensional Lumber 

0.00 

0.01 

0.01 

0.02 

Medium-density Fiberboard 

0.00 

0.01 

0.01 

0.02 

Food Discards 

0.00 

0.01 

0.01 

0.02 

Yard Trimmings 

Mixed Paper b 

0.00 

0.01 

0.01 

0.02 

Broad Definition 

0.00 

0.01 

0.01 

0.02 

Residential Definition 

0.00 

0.01 

0.01 

0.02 

Office Paper Definition 

0.00 

0.01 

0.01 

0.02 

Mixed MSW 

0.10 

0.01 

0.01 

0.12 

Carpet 

0.47 

0.00 

0.01 

0.48 

Personal Computers 

0.10 

0.00 

0.01 

0.11 

Tires 

2.05 

0.00 

0.01 

2.06 


Note that totals may not sum due to independent rounding, and more digits may be displayed than are significant. 
^The values for Phonebooks and textbooks are proxies, based on newspaper and office paper, respectively. 

The summary values for mixed paper are based on the proportions of the four paper types (corrugated cardboard, 
magazines/third-class mail, newspaper, and office paper) that constitute the different "mixed paper" definitions. 


70 








Exhibit 5-2 

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Next, losses in transmission and distribution of electricity were considered. Using a transmission 
and distribution loss rate of 5 percent, 2 EPA estimated that 523 kWh are delivered per ton of waste 
combusted at mass bum facilities, and 544 kWh are delivered per ton of waste input at RDF facilities 

EPA then used the value for the delivered kWh per ton of waste combusted to derive the implicit 
combustion system efficiency (i.e., the percentage of energy in the waste that is ultimately delivered in 
the form of electricity). To determine this efficiency, the Btu of MSW needed to deliver 1 kWh of 
electricity was estimated. EPA divided the Btu per ton of waste by the delivered kWh per ton of waste to 
obtain the Btu of waste per delivered kWh. The result is 19,200 Btu per kWh for mass bum and 21,000 
Btu per kWh for RDF. The physical constant for the energy in 1 kWh (3,412 Btu) then was divided by 
the Btu of MSW and RDF needed to deliver 1 kWh, to estimate the total system efficiency at 17.8 percent 
for mass bum and 16.3 percent for RDF (Exhibit 5-2, columns “d” and “e”). 2s 

Electric utility carbon emissions avoided : To estimate the avoided utility C0 2 from waste 
combustion, EPA used the results in columns “c” and “d,” together with a “carbon coefficient” of 0.081 
MTCE emitted per million Btu of utility-generated electricity (delivered), based on the national average 
fossil fuel mix used by utilities 20 as shown in Exhibit 5-3 and Exhibit 5-5. This approach uses the average 
fossil fuel mix as a proxy for the fuels displaced at the margin when utility-generated electricity is 
displaced by electricity from WTE plants. In other words, EPA assumes that nuclear, hydropower, and 
other nonfossil sources generate electricity at essentially fixed rates; marginal demand is met by fossil 
sources. 30 (In practice, the type of fuel displaced at the margin is not always fossil, with varying 
consequences on carbon reductions.) The resulting estimates for utility carbon emissions avoided for 
each material are shown in columns “g” and “h” of Exhibit 5-2. 

5.1.6 Approach to Estimating C0 2 Emissions Avoided Due to Steel Recycling 

Next, the study estimated the avoided C0 2 emissions from increased steel recycling made 
possible by steel recovery from WTE plants for (1) mixed MSW and (2) steel cans. Note that EPA did 
not credit increased recycling of nonferrous materials, because of lack of data on the proportions of those 
materials being recovered. The result tends to overestimate net GHG emissions from combustion. 

For mixed MSW, EPA estimated the amount of steel recovered per ton of mixed MSW 
combusted, based on (1) the amount of MSW combusted in the United States, and (2) the amount of steel 
recovered, postcombustion. Ferrous metals are recovered at approximately 89 WTE facilities in the 
United States and at five RDF processing facilities that do not generate power on-site. These facilities 
recovered a total of nearly 706,000 tons per year of ferrous metals in 2004. 31 By dividing 706,000 tons 
(total U.S. steel recovery at combustors) by total U.S. combustion of MSW, which is nearly 29 million 
tons, EPA estimated that 0.03 tons of steel are recovered per ton of mixed MSW combusted (as a national 
average). 


27 • . 

“ Personal communication among representatives of Integrated Waste Services Association, American Ref-Fuel, 
and ICF Consulting, October 28, 1997. 

78 

Note that the total system efficiency is the efficiency of translating the energy content of the fuel into the energy 
content of delivered electricity. The estimated system efficiencies of 17.8 and 16.3 percent reflect losses in (1) 
converting energy in the fuel into steam, (2) converting energy in steam into electricity, and (3) delivering 
electricity. The losses in delivering electricity are the transmission and distribution losses, estimated at 5 percent. 

Value estimated using data from the Energy Information Administration, Annual Energy> Review 2004 
(Washington, DC: U.S. Government Printing Office, DOE/EIA-0384(2000)), 2005. 

30 Nonfossil sources are expected to meet baseload energy requirements because of the financial incentive for these 
energy sources to generate at capacity. In general, the marginal cost of producing more power from these sources is 
minimal compared to the capital costs associated with establishing the facility. 

31 Integrated Waste Services Association, The 2004IWSA Waste-To-Energy Directory of United States Facilities. 


72 




For steel cans, EPA first estimated the national average proportion of steel cans entering WTE 
plants that would be recovered. As noted above, approximately 90 percent of MSW destined for 
combustion goes to facilities with a ferrous recovery system. At these plants, approximately 98 percent of 
the steel cans are recovered. EPA multiplied these percentages to estimate the weight of steel cans 
recovered per ton of MSW combusted—about 0.88 tons recovered per ton combusted. 

Finally, to estimate the avoided C0 2 emissions due to increased recycling of steel, EPA 
multiplied (1) the weight of steel recovered by (2) the avoided C0 2 emissions per ton of steel recovered. 
The result was estimated avoided C0 2 emissions of approximately 0.43 MTCE per ton for steel cans and 
0.01 MTCE per ton for mixed MSW, as shown in column “d” of Exhibit 5-5. 


Exhibit 5-3 

Estimating the Weighted Average Carbon Coefficient of the U.S. Average Mix of Fuels Used to Generate 



Electricity (MTCE/Million 

Btu) 



Primary Energy 

Percentage of 

Percentage of 

Carbon 
Coefficents b 
(Kg CE Emitted Per 


Consumption 3 

Generation: All 

Generation: Fossil 

Million Btu 

Fuel 

(Quads) 

Fuels (%) 

Fuels (%) 

Consumed) 

Coal c 

20.6 

50.5% 

73% 

25.72 

Natural Gas 

6.2 

15.2% 

22% 

14.33 

Petro!eum d 

1.3 

3.1% 

5% 

21.28 

Nuclear 

8.2 

20.2% 


0 

Renewable 

4.3 

10.5% 


0 

Other 

0 

0.5% 


0 

Total 

40.8 

100% 

100% 

NA 

Weighted Average - 
All Fuels 

Weighted Average - 
Fossil Fuels 




15.83 

23.01 


Note that totals may not sum due to independent rounding, and more digits may be displayed than are significant. 
a Source: ElA's Annual Energy Review: 2004, "Electricity Flow," for 2004. 
b Values include fugitive CH 4 emissions (weighted by the GWP of CH 4 ). 
c Carbon coefficient based on 49% bituminous, 43% sub-bituminous; 8% lignite. 
d The carbon coefficient for residual fuel is used as a proxy for petroleum. 


73 











Exhibit 5-4 

Estimating the Emission Factor for Utility Generated Electricity 







National 


Primary 



Fossil-Only 

Average 


Energy 

Electricity Net 

Implied Heat 

Weighted Heat 

Weighted Heat 


Consumption 

Generation 

Rate 

Rate 

Rate 

Fuel 

(Quads) 3 

(BkWh) 3 

(Btu/kWh) 

(Btu/kWh) b 

(Btu/kWh) b 

Coal 

20.6 

1,954 

10,532 

7,730 

5,319 

Natural Gas 

6.2 

619 

9,990 

2,202 

1,515 

Petroleum 

1.3 

113 

11,378 

519 

357 

Nuclear 

8.2 

789 

10,436 


2,108 

Renewable 

4.3 

315 

13,564 


1,421 

Other 

0 





Total 

40.8 










National 



Electricity Generation Fuel Mix 

Fossil-Only 

Average 


Generated Electricity Average Heat Rate (Btu/kWh) c 

10,451 

10,721 


Average Fuel Mix Carbon Coefficient (kg CE/MMBtu) d 

23.01 

15.83 


Generated Electricity Emission Factor (kg CE/kWh) e 

0.24 

0.17 


Generated Electricity Emission Factor (kg CE/MMBtu) f 

70.49 

49.75 


Generated Electricity Emission Factor (MTCE/MMBtu) 

0.070 

0.05 


a EIA. 2005. Annual Energy Review: 2004. (Table 8.4a and 8.2b) 
b Weighted by percent of total primary energy consumption. 
c Sum of the weighted heat rate values for each fuel type above. 
d Carbon coefficient weighted average by primary energy consumption (See table 5-3) 

e Average heat rate multiplied by the average fuel mix carbon coefficient. (National average value is equal to 1.37 pounds C0 2 E/kWh) 
1 Converted from kWh to Btu using the heatless constant of 3,412 Btu/kWh. 


74 











Exhibit 5-5 

Avoided GHG Emissions Due to Increased Steel Recovery from MSW at WTE Facilities 


(a) 

Material Combusted 

(b) 

Tons of Steel 
Recovered Per Ton 
Of Waste 

Combusted (Tons) 

(C) 

Avoided C0 2 
Emissions Per Ton 
Of Steel Recovered 
(MTCE/Ton) 

(d) 

Avoided C0 2 
Emissions Per Ton 
Of Waste 
Combusted 
(MTCE/Ton) a 

Aluminum Cans 

0.00 

0.00 

0.00 

Steel Cans 

0.88 

0.49 

0.43 

Copper Wire 

0.00 

0.00 

0.00 

Glass 

0.00 

0.00 

0.00 

HDPE 

0.00 

0.00 

0.00 

LDPE 

0.00 

0.00 

0.00 

PET 

0.00 

0.00 

0.00 

Corrugated Cardboard 

0.00 

0.00 

0.00 

Magazines/Third-class Mail 

0.00 

0.00 

0.00 

Newspaper 

0.00 

0.00 

0.00 

Office Paper 

0.00 

0.00 

0.00 

Phonebooks 

0.00 

0.00 

0.00 

Textbooks 

0.00 

0.00 

0.00 

Dimensional Lumber 

0.00 

0.00 

0.00 

Medium-density Fiberboard 

0.00 

0.00 

0.00 

Food Discards 

0.00 

0.00 

0.00 

Yard Trimmings 

0.00 

0.00 

0.00 

Mixed Paper b 




Broad Definition 

0.00 

0.00 

0.00 

Residential Definition 

0.00 

0.00 

0.00 

Office Paper Definition 

0.00 

0.00 

0.00 

Mixed MSW 

0.03 

0.49 

0.01 

Carpet 

0.00 

0.00 

0.00 

Personal Computers 

0.25 

0.49 

0.12 

Tires 0 

0.06 

0.49 

0.03 


Note that totals may not sum due to independent rounding, and more digits may be displayed than are significant. 
a The value in column "d" is a national average and is weighted to reflect 98 percent recovery at the 90 percent of facilities 
that recover ferrous metals. 

b The summary values for mixed paper are based on the proportions of the four paper types (corrugated cardboard, 
magazines/third-class mail, newspaper, and office paper) that constitute the different mixed paper definitions. 

c Assumes only 48 percent of facilities that use TDF recover ferrous metals. 


75 








5.2 RESULTS 


The results of this analysis are shown in Exhibit 5-6. The results from the last column of Exhibit 
5-1, the last two columns of Exhibit 5-2, and the last column of Exhibit 5-5 are shown in columns “b” 
through “e” in Exhibit 5-6. The net GHG emissions from combustion of each material at mass bum and 
RDF facilities are shown in columns “f ’ and “g,” respectively. These net values represent the gross GEIG 
emissions (column “b”), minus the avoided GHG emissions (columns “c,” “d,” and “e”). As stated 
earlier, these estimates of net GHG emissions are expressed for combustion in absolute terms. They are 
not values relative to some other waste management option. They are expressed in terms of short tons of 
waste input (i.e., tons of waste prior to processing). 

EPA estimates that combustion of mixed MSW at mass bum and RDF facilities reduces net 
postconsumer GHG emissions to -0.03 and -0.02 MTCE per ton, respectively. Combustion of paper 
products has negative net postconsumer GHG emissions ranging from -0.13 to -0.20 MTCE per ton at 
mass bum facilities and from -0.12 to -0.18 MTCE per ton at RDF facilities. Net GHG emissions are 
negative because CO; emissions from burning paper are not counted (because they are biogenic) and 
fossil fuel burning by utilities to generate electricity is avoided. Likewise, combustion of medium-density 
fiberboard and dimensional lumber also results in negative net GHG emissions, with both equaling -0.21 
MTCE per ton at mass bum facilities and -0.19 MTCE per ton at RDF facilities. Finally, net GHG 
emissions for food discards and yard trimmings (two other forms of biomass) are also negative, but of a 
smaller magnitude (-0.05 and -0.06 MTCE per ton of material, respectively, for mass bum and -0.04 and - 
0.05 MTCE per ton of material, respectively, for RDF). 

Combustion of plastics results in substantial net GHG emissions, estimated from 0.25 to 0.30 
MTCE per ton of material combusted for mass bum facilities, and from 0.30 to 0.32 MTCE per ton of 
material input to RDF facilities. This result is primarily because of the high content of nonbiomass 
carbon in plastics. Also, when combustion of plastic results in electricity generation, the utility carbon 
emissions avoided (due to displaced utility fossil fuel combustion) are much lower than the carbon 
emissions from the combustion of plastic. This result is largely due to the lower system efficiency of 
WTE plants, compared with electric utility plants. Recovery of ferrous metals at combustors results in 
negative net GHG emissions, estimated at -0.42 MTCE per ton of steel cans, due to the increased steel 
recycling made possible by ferrous metal recovery at WTE plants. 

5.3 LIMITATIONS 

The certainty of the analysis presented in this chapter is limited by the reliability of the various 
data elements used. The most significant limitations are as follows: 

• Combustion system efficiency of WTE plants may be improving. If efficiency improves, more 
utility CO; will be displaced per ton of waste combusted (assuming no change in utility emissions 
per kWh), and the net GHG emissions from combustion of MSW will decrease. 

• Data for the RDF analysis were provided by the Minnesota Office of Environmental Assistance 
and were obtained from a single RDF processing facility and a separate RDF combustion facility. 
Research indicates that each RDF processing and combustion facility is different. For example, 
some RDF combustion facilities may generate steam for sale off-site, which can affect overall 
system efficiency. In addition, the amount of energy required to process MSW into RDF and the 
amount of energy used to operate RDF combustion facilities can be difficult to quantify and can 
vary among facilities on a daily, seasonal, and annual basis. Thus, the values used for the RDF 
analysis should be interpreted as approximate values. 


76 


Exhibit 5-6 

Net GHG Emissions from Combustion at WTE Facilities 


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The reported ranges for N 2 O emissions were broad. In some cases the high end of the range was 
10 times the low end of the range. Research has indicated that N 2 0 emissions vary with the type of waste 
burned. Thus, the average value used for mixed MSW and for all MSW components should be 
interpreted as an approximate value. 

• For mixed MSW, the study assumed that all carbon in textiles is from synthetic fibers derived 
from petrochemicals (whereas, in fact, some textiles are made from cotton, wool, and other 
natural fibers). Because EPA assumed that all carbon in textiles is nonbiogenic, all of the C0 2 
emissions from combustion of textiles as GHG emissions were counted. This assumption will 
slightly overstate the net GHG emissions from combustion of mixed MSW, but the magnitude of 
the error is small because textiles represent only a small fraction of the MSW stream. Similarly, 
the MSW category of “rubber and leather” contains some biogenic carbon from leather and 
natural rubber. By not considering this small amount of biogenic carbon, the analysis slightly 
overstates the GHG emissions from MSW combustion. 

• Because the makeup of a given community’s mixed MSW may vary from the national average, 
the energy content also may vary from the national average energy content used in this analysis. 
For example, MSW from communities with a higher- or lower-than-average recycling rate may 
have a different energy content, and MSW with more than the average proportion of dry leaves 
and branches will have a higher energy content. 

• In this analysis, EPA used the national average recovery rate for steel. Where waste is sent to a 
WTE plant with steel recovery, the net GHG emissions for steel cans will be slightly lower (i.e., 
more negative). Where waste is sent to a WTE plant without steel recovery, the net GHG 
emissions for steel cans will be the same as for aluminum cans (i.e., close to zero). EPA did not 
credit increased recycling of nonferrous materials, because of a lack of information on the 
proportions of those materials. This assumption tends to result in overstated net GHG emissions 
from combustion. 

• This analysis used the national average fossil fuel mix for electricity as the proxy for fuel 
displaced at the margin when WTE plants displace utility electricity. If some other fuel or mix of 
fuels is displaced at the margin (e.g., coal), the avoided utility C0 2 would be different (e.g., for 
coal, the avoided utility C0 2 would be about 0.01 MTCE per ton higher for mixed MSW, and the 
net GHG emissions would be -0.04 MTCE instead of-0.03 MTCE per ton). 


78 


6. LANDFILLING 


This chapter presents estimates of GHG emissions and carbon storage from landfilling the 
materials considered in this analysis. For this study, EPA estimated the CH 4 emissions, transportation- 
related CO 2 emissions, and carbon storage that will result from landfilling each type of organic waste and 
mixed MSW. The analysis is based on three key GHG accounting principles: 1 

• When food discards, yard trimmings, paper, and wood are landfilled, anaerobic bacteria degrade 
the materials, producing CH 4 and C0 2 . CH 4 is counted as an anthropogenic GHG, because even 
though it is derived from sustainably harvested biogenic sources, degradation would not result in 
CH 4 emissions if not for deposition in landfills. The C0 2 is not counted as a GHG in this context 
because if it were not emitted from landfills, it would be produced through natural decomposition. 
Because metals and glass do not contain carbon, they do not generate CH 4 when landfilled. 
Plastics, carpet, PCs, clay bricks, concrete, fly ash, and tires do not biodegrade measurably in 
anaerobic conditions, and therefore do not generate any CH 4 . 

• Transportation of waste materials to a landfill results in anthropogenic C0 2 emissions, due to the 
combustion of fossil fuels in the vehicles used to haul the wastes. 

• Because food discards, yard trimmings, and paper are not completely decomposed by anaerobic 
bacteria, some of the carbon in these materials is stored in the landfill. Because this carbon 
storage would not normally occur under natural conditions (virtually all of the organic material 
would degrade to C0 2 , completing the photosynthesis/respiration cycle), this is counted as an 
anthropogenic sink. However, carbon in plastic that remains in the landfill is not counted as 
stored carbon, because it is of fossil origin. 

EPA developed separate estimates of emissions from (1) landfills without gas recovery systems, 
(2) those that flare CH 4 , (3) those that combust CH 4 for energy recovery, and (4) the national average mix 
of these three categories. The national average emission estimate accounts for the extent to which CH 4 
will be flared at some landfills and combusted onsite 2 3 for energy recovery at others/ 

From the standpoint of postconsumer GHG emissions, landfilling some materials—including 
newspaper and phonebooks—results in net storage (i.e., carbon storage exceeds CH 4 plus transportation 
energy emissions) at all landfills, regardless of whether gas recovery is present. At the other extreme, 
office paper, textbooks, and food discards result in net emissions regardless of landfill gas collection and 
recovery practices. The remaining materials have net postconsumer emissions that are either very low (all 
materials have transportation-related emissions of 0.01 MTCE per ton, regardless of whether gas 
collection is present) or borderline, depending on whether the landfill has gas recovery (e.g., mixed MSW 
has net emissions at landfills without gas recovery, but net carbon storage at landfills with gas recovery). 


1 These principles are described in broad terms in Section 1.4 of this report. 

- Although gas from some landfills is piped to an offsite power plant and combusted there, for the purposes of this 
report, the assumption was that all gas for energy recovery was combusted onsite. 

3 Currently, most landfill CH 4 recovery in the United States—both for flaring and electricity—is occurring in 
response to a 1996 EPA rule that requires a well-designed and well-operated landfill gas collection system at 
landfills that (1) have a design capacity of at least 2.5 million metric tons and 2.5 million cubic meters, (2) are 
calculated to emit more than 50 metric tons of non-CH 4 organic compounds per year; and (3) received waste on or 
after November 1 1, 1987 {Federal Register , Vol. 61, No. 49, p. 9905, March 12, 1996). For the year 2003, an 
estimated 59 percent of landfill CH 4 was generated at landfills with landfill gas recovery systems subject to these 
requirements or installed on a voluntary basis (U.S. Environmental Protection Agency, 2005. Inventory ofU.S. 
Greenhouse Gas Emissions and Sinks: 1990-2003). 


79 





6.1 ch 4 generation and carbon storage for organic materials 

This section starts with a review of the principal processes that influence the fate of organic 
carbon in the landfill environment and then describes the experimental basis for and derivation of the 
estimates of CH 4 emissions and carbon storage used in this report. 

6.1.1 Carbon Stocks and Flows in Landfills 

Exhibit 6-1 shows the carbon flows within a landfill system. Carbon entering the landfill can 
have one of several fates: exit as CH 4 , exit as CO 2 , exit as volatile organic compounds (VOCs), exit 
dissolved in leachate, or remain stored in the landfill. 4 * 

After entering landfills, a portion of the organic materials decomposes and eventually is 
transformed into landfill gas and/or leachate. Aerobic bacteria initially decompose the waste until the 
available oxygen is consumed. This stage usually lasts less than a week and is followed by the anaerobic 
acid state, in which carboxylic acids accumulate, the pH decreases, and some cellulose and hemicellulose 
decomposition occurs. Finally, during the methanogenic state, bacteria further decompose the organic 
material into CH 4 and CO 2 . 

The rate of decomposition in landfills is affected by a number of factors, including: (1) waste 
composition; (2) factors influencing microbial growth (moisture, available nutrients, pH, temperature); 
and (3) whether the operation of the landfill retards or enhances waste decomposition. Most studies have 
shown the amount of moisture in the waste, which can vary widely within a single landfill, to be a critical 
factor in the rate of decomposition. " As a result, there is increasing interest in the operation of landfills as 
bioreactors, in which leachate and possibly other liquids are recirculated to enhance decomposition and 
gas production. 6 Bioreactor technologies, which optimize landfill moisture content in order to accelerate 
waste decomposition, have emerged as a leading technology for facilitating rapid decomposition of 
organic wastes and cost-effective CH 4 collection. 

Of the various components of the landfill carbon system, by far the most research to date has been 
conducted on the transformation of landfill carbon into CH 4. 7 ’ 8 This interest has been spurred by a 
number of factors, including EPA’s 1996 rule requiring large landfills to control landfill gas emissions 
(40 Code of Federal Regulations Part 60, Subparts Cc and WWW), the importance of CH 4 emissions in 
GHG inventories, and the market for CH 4 as an energy source. CH 4 production occurs in the 
methanogenic stage of decomposition, as methanogenic bacteria break down the fermentation products 
from earlier decomposition processes. Since CH 4 emissions result from waste decomposition, the 
quantity and duration of the emissions is dependent on the same factors that influence waste degradability 
(e.g., waste composition, moisture). 


4 The exhibit and much of the ensuing discussion are taken directly from Freed, J.R., K. Skog, C. Mintz, and N. 
Glick. 2004. “Carbon Storage due to Disposal of Biogenic Materials in U.S. Landfills.” Proceedings of the Third 
Annual Conference on Carbon Sequestration , U.S. Department of Energy. Available at www.carbonsq.com. 

Barlaz, M. A., R.K. Ham, and D.M. Schaefer. 1990. “Methane Production From Municipal Refuse: A 
Review of Enhancement Techniques and Microbial Dynamics,” Critical Reviews in Environmental Control , 

19(6):557. 

6 Pacey, J., D. Augenstein, R. Morck, D. Reinhart, R. Yazdani. 1999. The Bioreactive Landfill. MSW Management, 
September/October 1999. 

7 Bingemer, H G. and P J Crutzen, 1987. “The Production of Methane from Solid Wastes.” Journal of Geophysical 
Research 90(D2): 2181-2187. 

x Barlaz, M„ W. Eleazer, W. Odle, X. Qian, Y. Wang. 1997. “Biodegradative Analysis of Municipal Solid Waste in 
Laboratory-Scale Landfills,” U.S. Environmental Protection Agency 600/R-97-071. 


80 



Exhibit 6-1 Landfill Carbon Mass Balance 



Recovery 

«Vi 


<2v 


CH, CO ? VOCs 


Carbon 

Storage 

Lignin, biomass, 
undeoomposed cellulose 
and tamlceltulose. etc 


Leachate Coaetctlon 


Carbon 

InDuts 


Carbon dioxide is produced in the initial aerobic stage and anaerobic acid stage of decomposition. 
However, relatively little research has been conducted to quantify C0 2 emissions during these stages. 
Emissions during the aerobic stage are generally assumed to be a small proportion of total organic carbon 
inputs, and a screening level analysis indicates that less than 1 percent of carbon is likely to be emitted 
through this pathway. 9 Once the methanogenic stage of decomposition begins, landfill gas as generated 
is composed of approximately 50 percent CH 4 and 50 percent C0 2 . 10 But landfill gas as collected 
generally has a higher CH 4 concentration than C0 2 concentration (sometimes as much as a 60 percent:40 
percent ratio), because some of the C0 2 is dissolved in the leachate as part of the carbonate system (C0 2 
«-♦ h 2 co 3 <-► HC0 3 ' *-> C0 3 2 ). 

To date, very little research has been conducted on the role of VOC emissions in the landfill 
carbon mass balance. Given the thousands of compounds entering the landfill environment, tracking the 
biochemistry by which these compounds ultimately are converted to VOC is a complex undertaking. 
Existing research indicates that ethane, limonene, ??-decane, /7-dichlorobenzene, and toluene may be 


9 Freed et al. 2004. Op cit. 

10 Bingemer, H. G. and P. J. Crutzen, 1987. Op. cit. 


81 













among the most abundant landfill VOCs. 11 Hartog (2003) reported non-CH 4 volatile organic compound 
concentrations in landfill gas at a bioreactor site in Iowa, averaging 1,700 parts per million (ppm) carbon 
by volume in 2001 and 925 ppm carbon by volume in 2002. 12 If the VOC concentrations in landfill gas 
are generally of the order of magnitude of 1,000 ppm, VOCs would have a small role in the overall 
carbon balance, as concentrations of CH 4 and C0 2 will both be hundreds of times larger. 

Leachate is produced as water percolates through landfills. Factors affecting leachate formation 
include the quantity of water entering the landfill, waste composition, and the degree of decomposition. 
Because it may contain materials capable of contaminating groundwater, leachate (and the carbon it 
contains) is typically collected and treated before being released to the environment, where it eventually 
degrades into CCF. However, leachate is increasingly being recycled into the landfill as a means of 
inexpensive disposal and to promote decomposition while the containment system is operating at peak 
efficiency. 13 Research shows that this recirculation can increase the mass of organics collected by the 
system and consequently enhance aqueous degradation. 14 Although a significant body of literature exists 
on landfill leachate formation, little research is available on the carbon implications of this process. 

Based on a screening analysis, Freed et al. (2004) found that loss as leachate may occur for less than one 
percent of total carbon inputs to landfills. 

In mass balance terms, carbon storage can be characterized as the carbon that remains after 
accounting for the carbon exiting the system as landfill gas or dissolved in leachate. On a dry weight 
basis, municipal refuse contains 30-50 percent cellulose, 7-12 percent hemicellulose, and 15-28 percent 
lignin.Although the degradation of cellulose and hemicellulose in landfills is well documented, lignin 
does not degrade to a significant extent under anaerobic conditions. 16 In fact, although cellulose and 
hemicellulose biodegradation does occur, the extent of decomposition varies with landfill conditions, and 
these materials do not appear to completely degrade based on a number of excavation studies. * 1 In 
addition, the presence of lignin actually prevents some cellulose and hemicellulose biodegradation. Thus, 
landfills in effect store some of the cellulose and hemicellulose and all of the lignin that is buried initially. 
The amount of storage will vary with environmental conditions in the landfill; pH and moisture content 
have been identified as the two most important variables controlling decomposition. 18 

6.1.2 Measured and Estimated CH 4 Generation and Carbon Storage 

The focus of this report is on comparing waste management options for specific materials within 
the solid waste stream. Although a large body of research exists on CH 4 generation from mixed solid 
wastes, only a few investigators—most notably Dr. Morton Barlaz and coworkers at North Carolina State 
University—have measured the behavior of specific waste wood, paper, food waste, and yard trimming 
components. 


" Eklund B„ E. Anderson, B. Walker, and D. Burrows.1998. “Characterization of landfill gas composition at the 

Fresh Kills municipal solid-waste landfill.” Environ Sci Technol 32:2233-2237. 

1 •> 

" Hartog, C.L. 2003. The Bluestem Bioreactor. Briefing presented at the Bioreactor Workshop, sponsored by 
USEPA, Feb 27-28, 2003, Arlington, VA. 

1 Chan G., L. Chu, and M. Wong. 2002. “Effects of leachate recirculation on biogas production from landfill co¬ 
disposal of municipal solid waste, sewage sludge and marine sediment.” Environmental Pollution 118(3). 393-399. 

14 Warith, M. A., W. Zekry, and N. Gawri. 1999. “Effect of leachate recirculation on municipal solid waste 
biodegradation,” Water Quality Research Journal of Canada Volume 34, No. 2, pp. 267-280. 

15 Hilger, H., and M. Barlaz. 2001. “Anaerobic decomposition of refuse in landfills and methane oxidation in 
landfill cover soils,” Manual of Environmental Microbiology , 2nd Ed., Am. Soc. Microbiol., Washington, D C pp 
696-718. 

Colberg, P.J. 1988. Anaerobic microbial degradation of cellulose lignin, oligolignols, and monoaromatic lignin 
derivatives, p. 333-372. In A.J.B. Zehnder (ed.) Biology of anaerobic microorganisms. New York: Wiley. 

Ham, R.K., and Bookter T.J. 1982. "Decomposition of solid waste in test lysimeters.” J.Env. Eng. 108: 1147. 

18 Barlaz, M. A., R. Ham, and D. Schaefer. 1990. Op cit. 


82 



Barlaz 14 developed a series of laboratory experiments designed to measure biodegradation of 
these materials in a simulated landfill environment, in conditions designed to promote decomposition 
(i.e., by providing ample moisture and nutrients). Specific waste components (e.g., grass, branches, 
leaves, paper) were dried, analyzed for cellulose, hemicellulose, and lignin content, weighed, placed in 
two-liter plastic containers (i.e., reactors), and allowed to decompose anaerobically under moist 
conditions (Eleazer, et al. 1997). 20 The reactors were seeded with a small amount of well-decomposed 
refuse containing an active population of microorganisms. Phosphate and nitrogen concentrations were 
maintained at sufficient levels to assure that they were not limiting factors for biodegradation. The 
reactors were allowed to run until either no more CH 4 was produced or an extrapolation of gas production 
data indicate that the reactors had produced 95 percent of the CH 4 that would ultimately be emitted if 
allowed to run forever. At the end of the experiment, the contents of the reactors were dried, weighed, 
and analyzed for cellulose, hemicellulose, lignin, and (in the case of grass only) protein content. The 
carbon in these residual components is assumed to represent carbon that would remain undegraded over 
the long term in landfills; i.e., it would be stored. 

Thus, these experiments provide three key outputs on a material-by-material basis: initial carbon 
content (namely, the sum of carbon in the cellulose, hemicellulose, lignin, and protein components), 
cumulative CH 4 emissions (over the course of the experiment), and carbon stored (as of the end of the 
experiment). 21 

As described in the preceding section, the principal elements in the landfill carbon balance are: 

• Initial carbon content; 

• Carbon output as CH 4 (CH 4 -C); 

• Carbon output as C0 2 (C0 2 -C); and 

• Residual carbon (i.e., landfill carbon storage, LF C). 

Of these elements, the only one missing in the Barlaz experiments is C0 2 emissions. In a simple system 
where the only carbon fates are CH 4 , C0 2 , and carbon storage, the carbon balance can be described as 

CH 4 - C + C0 2 - C + LF C = Initial C 

If the only decomposition is anaerobic, then CH 4 -C = C0 2 -C. 22 Thus, the carbon balance can be 
expressed as 

2 x CH 4 - C + LF C = Initial C 

Exhibit 6-2 shows the measured experimental values, in terms of the percentage of initial carbon, 
for each of the materials analyzed (see columns “b” and “d”). The exhibit also displays the implied 
biogas yield (= 2 x CH 4 - C, column “c”), and the sum of outputs (= 2 x CH 4 - C + LF C) as a percentage 
of initial carbon (see column “e”). As column “e” shows, the balance between carbon outputs and carbon 
inputs generally was not perfect; the imbalance ranges from 0 percent of initial carbon for newsprint to 34 
percent of initial carbon for office paper, and is attributable to measurement uncertainty in the analytic 
techniques. 


19 Barlaz, M.A., 1998. “Carbon storage during biodegradation of municipal solid waste components in laboratory- 
scale landfills.” Global Biogeochemical Cycles 12 (2), 373-380. 

20 Eleazer, W.E., W.S. Odle, III, Y.S. Wang, and M.A. Barlaz. 1997. “Biodegradability of municipal solid waste 
components in laboratory-scale landfills.’ Env. Sci. Tech. 31(3).911—917. 

21 It should be noted that VOCs are also emitted, but are estimated to account for less than one percent of carbon 
flux from landfills. (Freed, J.R., K. Skog, N. Glick, C. Mintz. 2004. Carbon Storage due to Disposal of Biogenic 
Materials in U.S. Landfills. Proceedings of the Third Annual Conference on Carbon Sequestration. U.S. Dept of 
Energy, National Energy Technology Lab.) 

22 The molar ratio of CH 4 to CO, is 1:1 for carbohydrates (e.g., cellulose, hemicellulose). For proteins, the molar 
ratio is 1.65 CH 4 per 1.55 C0 2 ; for protein it is C 3 . 2 H 5 ON 0.86 (Barlaz et al. 1989). Given the predominance of 
carbohydrates, for all practical purposes, the overall ratio is 1.1. 


83 



For the emission factors used in this report, adjustments were made to the measured values so that 
exactly 100 percent of the initial carbon would be accounted for. After consultation with Dr. Barlaz, the 
following approach was adopted: 

• For materials where carbon outputs were less than initial carbon, the “missing carbon was 
assumed to be emitted as equal molar quantities of CH 4 and C0 2 . In these cases (corrugated 
cardboard, office paper, food discards, leaves, branches, and mixed MSW) the CH 4 -C was 
increased with respect to the measured values as follows: 

(Initial C - LF C) / 2 = CH 4 - C 

This calculation assumes that C0 2 -C = CH 4 -C. In essence, the adjustment approach was to 
increase biogas production. The resulting values are italicized in column “g” of Exhibit 6-2. 

• For materials where carbon outputs were greater than initial carbon (coated paper and grass), the 
measurements of initial carbon content and CH 4 mass were assumed to be accurate. Here, the 
adjustment approach was to decrease carbon storage. Thus, landfill carbon storage was calculated 
as the residual of initial carbon content minus (2 x CH 4 -C). The resulting values are italicized in 
column “h” of Exhibit 6-2. 


Exhibit 6-2 

Experimental and Adjusted Values for CH 4 Yield and Carbon Storage. 3 



Initial 
Carbon 
Content, % 

Of dry 
Matter 

Measured 
Yield as a % 

Of Initial 
Carbon 

Implied Yield 

Of Biogas 
(CH 4 +C0 2 ) as 
Proportion Of 
Initial Carbon 

Measured 
Proportion of 
Initial Carbon 
Stored 

Output as 
%of 
Initial 
Carbon 

Adjustment 

Approach 

Adjusted 
Yield of CH 4 
as Proportion 
Of Initial 
Carbon 

Adjusted 

Proportion 

Of Initial 
Carbon 
Stored 


a 

b 

c(=2«b) 

d 

e(=c+d) 

f 

9 

h 

Paper and 
Paperboard 









Corrugated 

46% 

16% 

32% 

55% 

88% 

inc biogas 

22% 

55% 

Newsprint 

49% 

8% 

15% 

85% 

100% 

NA 

8% 

85% 

Office Paper 

40% 

27% 

54% 

12% 

66% 

inc biogas 

44% 

12% 

Coated Paper 

34% 

12% 

25% 

99% 

124% 

reduce LF C 

12% 

75% 

Food Discards 

50% 

30% 

59% 

16% 

75% 

inc biogas 

42% 

16% 

Yard Trimminqs 









Grass 

44% 

16% 

32% 

71% 

103% 

reduce LF C 

16% 

68% 

Leaves 

41% 

7% 

14% 

72% 

86% 

inc biogas 

14% 

72% 

Branches 

49% 

6% 

13% 

77% 

90% 

inc biogas 

12% 

77% 

MSW 

42% 

11% 

22% 

52% 

74% 

inc biogas 

24% 

52% 


g 

CH 4 generation estimates are from Eleazer, et al. (1997), op cit. Carbon storage and initial carbon content values are from Barlaz 
(1998), op cit. All values for leaves (initial carbon content, CH 4 generation, and carbon storage) are from updated experiments 
reported in a letter report from M.A. Barlaz to J.R. Freed (of ICF Consulting) dated June 29, 2005. 


84 






















Exhibit 6-3 

CH 4 Yield for Solid Waste Components 


Material 

Initial 

Carbon 

Content 

(%) 

Final (Adjusted) 

C Emitted as 
CH 4 (%) 

Final (Adjusted) 
CH 4 Yield 
(MTCE/dry ton) 

Final (Adjusted) 
CH 4 Yield 
(MTCE/wet ton) 

Corrugated Cardboard 

47 

22 

0.80 

0.688 

Magazines/Third-class Mail 

34 

12 

0.32 

0.278 

Newspaper 

49 

08 

0.28 

0.244 

Office Paper 

40 

44 

1.35 

1.198 

Food Discards 

51 

42 

1.63 

0.445 

Yard Trimmings 




0.264 

Grass 

45 

16 

0.55 

0.150 

Leaves 

49 

14 

0.44 

0.281 

Branches 

49 

12 

0.44 

0.355 

Mixed MSW 

42 

24 

0.76 

0.580 


Exhibit 6-4 



Carbon Storage 

For Solid Waste Components 


(a) 

(b) 

(c) 

(d) 

(e) 


Ratio Of Carbon 

Ratio Of Dry 

(d = b x c) Ratio 

Of Carbon 

Amount Of 


Storage to Dry 

Weight to Wet 

Storage to Wet 

Carbon Stored 


Weight (gm C/dry 

Weight (dry 

Weight (gm C/wet 

(MTCE per Wet 

Material 

gm) 

gm/wet gm) 

gm) 

Ton) 

Corrugated Cardboard 

0.26 

0.95 

0.25 

0.22 

Magazines/Third-class 

Mail 

0.26 

0.95 

0.25 

0.22 

Newspaper 

0.42 

0.95 

0.40 

0.36 

Office Paper 

0.05 

0.95 

0.05 

0.04 

Food Discards 

0.08 

0.30 

0.02 

0.02 

Yard Trimmings 

Grass 

0.30 

0.30 

0.09 

0.19 

0.08 

Leaves 

0.30 

0.70 

0.21 

0.19 

Branches 

0.38 

0.90 

0.34 

0.31 

Mixed MSW 

0.22 

0.84 

0.18 

0.17 


Explanatory Notes: 

(1) Because MSW is typically measured in terms of its wet weight, it was required to convert the ratios for carbon stored as a 
fraction of dry weight to carbon stored as a fraction of wet weight. To do this conversion, EPA used the estimated ratio of dry 
weight to wet weight for each material. These ratios are shown in column “c” of the exhibit. For most of the materials, EPA used 
data from an engineering handbook." 3 For grass, leaves, and branches, EPA used data provided by Dr. Barlaz. 

(2) For consistency with the overall analysis, EPA converted the carbon storage values for each material to units of MTCE stored 
per short ton of waste material landfilled. The resulting values are shown in column e of the exhibit. 

The CH 4 yields in column “g” of Exhibit 6-2 can be converted to yields expressed in MTCE/short 
ton (to be consistent with units in the rest of the report), as shown in Exhibit 6-3. Similarly, the carbon 
storage proportions listed in percentages in Exhibit 6-2 are converted to MTCE/wet ton in Exhibit 6-4. 

23 Tchobanoglous, George, Hilary Theisen, and Rolf Eliassen. 1977. Solid Wastes: Engineering Principles and 
Management Issues (New York: McGraw-Hill Book Co.), pp. 58 and 60. 


85 



















Dr. Barlaz’s experiment did not specifically test all of the paper grades described in this report. 

He did evaluate four specific grades: newspaper, corrugated boxes, office paper, and coated paper. EPA 
identified proxies for five additional material types for which there were no experimental data. 

Magazines and third-class mail placed in a landfill were assumed to have characteristics similar to those 
observed for coated paper. Similarly, phonebooks and textbooks were assumed to behave in the same 
way as newspaper and office paper, respectively. Experimental results for branches were used as a proxy 
for dimensional lumber and medium-density fiberboard. 

As discussed in Section 3.2, EPA included the following three definitions of mixed paper among 
the materials analyzed in this report: 

• Broadly defined mixed paper, which includes almost all printing-writing paper, folding boxes, 
and most paper packaging; 

• Residential mixed paper, which includes the typical mix of papers from residential curbside pick¬ 
up (e.g., high-grade office paper, magazines, catalogs, commercial printing, folding cartons, and a 
small amount of old corrugated containers); and 

• Mixed paper from offices, which includes copy and printer paper, stationary and envelopes, and 
commercial printing. 

To develop estimates of CH 4 emissions and carbon storage for these three categories of mixed 
paper, EPA used the detailed characterization of mixed paper (shown in Exhibit 3-2) developed by FAL, 
and assigned analogues among the four paper grades tested by Dr. Barlaz. Exhibit 6-5 characterizes the 
composition of the two products made from mixed paper: boxboard (made using either a broad or a 
residential mix of recycled paper) and paper towels (made from recycled office paper). Emissions were 
calculated using these characterizations of the mixed paper grades and the values obtained from Dr. 
Barlaz’s experiment for newspaper, corrugated boxes, office paper, and coated paper. 24 

6.2 FATES OF LANDFILL CH 4 

In this analysis, EPA accounted for (1) the oxidation in the landfill of some portion of landfill 
CH 4 to C0 2 , and (2) the capture of CH 4 , either for flaring or for combustion with energy recovery (in 
either case, the captured CH 4 is converted to C0 2 ). 25 Exhibit 6-6 presents this analysis. 

The exhibit begins with the CH 4 generation per wet ton of each material, which is shown in column “b” 
(the values were simply copied from the last column of Exhibit 6-3). Columns “c” through “k” calculate 
net GHG emissions from CH 4 generation for each of three categories of landfills: (1) landfills without 
LFG recovery; (2) landfills with LFG recovery that flare LFG; and (3) landfills with LFG recovery that 
generate electricity from the LFG. Columns “1" through “n” show CH 4 generation-weighted percentage 
for each category in 2004.“ 6 The final column shows the weighted average GHG emissions from CH 4 
generation across all types of landfills. 

To estimate MSW CH 4 emissions from each category of landfill, EPA first estimated the 
percentage of landfill CH 4 that is oxidized near the surface of the landfill. Based on estimates in the 
literature, EPA assumed that 10 percent of the landfill CH 4 generated is either chemically oxidized or 


" 4 Note that Exhibits 6-2 through 6-4 do not show mixed paper since this was not used as a category by Dr. Barlaz; 
however, mixed paper is shown in Exhibit 6-8 through Exhibit 6-10. 

“ The C0 2 that is emitted is not counted as a GHG because it is biogenic in origin (as described in “C0 2 Emissions 
from Biogenic Sources” in Section 1.4.2). 

26 U.S. Environmental Protection Agency, 2006. Inventory ofU.S. Greenhouse Gas Emissions and Sinks: 1990- 
2004. 


86 



converted by bacteria to C0 2 , 2 and the remaining 90 percent remains as CH 4 , and is either emitted or 
captured and burned. 


Exhibit 6-5 

Composition of Mixed Paper Categories from Barlaz Experiments (Percent) 


Paper Grade 

Broad Definition for 
Mixed Paper 

Mixed Paper from 
Residential Sources 

Mixed Paper from 
Offices 

Corrugated Cardboard 3 

48 

53 

5 

Magazines/Third-class 

Mail b 

8 

10 

36 

Newspaper 0 

24 

23 

21 

Office Paper d 

20 

14 

38 

Total 

100 

100 

100 


Explanatory Notes: 

a Includes virgin and recycled corrugated boxes. 
b Includes coated free sheet paper and coated groundwood paper. 

c Includes newspaper, uncoated groundwood paper, recycled folding boxes, and set-up boxes. 

d Includes uncoated free sheet paper, cotton fiber paper, bleached bristols, unbleached kraft folding boxes, bleached kraft folding 
boxes, bleached bags and sacks, unbleached bags and sacks, and unbleached wrapping paper. 


To estimate MSW CH 4 emissions from landfills with LFG recovery, EPA assumed that these 
landfills have an average LFG recovery efficiency of 75 percent. 2S EPA then calculated avoided utility 
GHG emissions from landfills where the CH 4 is used for electricity generation. Because energy recovery 
systems experience down time, during which CH 4 is flared rather than used to generate electricity, a 15 
percent system efficiency loss was incorporated into the estimates for avoided utility emissions. 24 

EPA also estimated the percentage of CFL* generated at each category of landfill in 2003. 
Research indicates that 59 percent of all landfill CFI 4 was generated at landfills with recovery systems, 
and the remaining 41 percent was generated at landfills without LFG recovery. 30 Of the 59 percent of all 
CH 4 generated at landfills with LFG recovery, 53 percent (or 31 percent of all CH 4 ) was generated at 
landfills that use LFG to generate electricity, and 47 percent (or 28 percent of all CH 4 ) at landfills that 
flare LFG. 31 ’ 32 

The results are shown in the final column of Exhibit 6-6. The materials with the highest rates of 
net GHG emissions from CH 4 generation, as shown in column “o”—corrugated boxes, office paper, and 


27 An oxidation rate of 10 percent is cited by Liptay, K„ J. Chanton, P. Czepiel, and B. Mosher, “Use of stable 
isotopes to determine methane oxidation in landfill cover soils,” Journal of Geophysical Research , April 1998, 
103(D7), pp. 8243-8250; and Czepiel, P.M., B. Mosher, P.M. Crill, and R.C. Harriss. 1996. “Quantifying the effects 
of oxidation on landfill methane emissions,” Journal of Geophysical Research , 101, pp. 16721-16729. The rate of 
10 percent is also recommended by the IPCC. 

28 EPA. 2005. The Landfill Methane Outreach Program (LMOP) has used this figure in its most recent publications 
[see, for example, U.S. Methane Emissions 1990-2020: Inventories, Projections, and Opportunities for Reductions 
(Washington, D.C.: U.S. Environmental Protection Agency) September 1999]. 

29 EPA. 1999. Landjill Gas-to-Energy Project Opportunities: Background Information on Landfill Profiles, Office 
of Air and Radiation, EPA 430-K-99-002, pp. 3-13. 

30 Based on data on year 2004 MSW landfill CH 4 generation and collection data from Inventory of U.S. Greenhouse 
Gas Emissions and Sinks: 1990-2004) with an estimated landfill CH 4 recovery efficiency of 75 percent (from U.S. 
Methane Emissions 1990-2020: Inventories, Projections, and Opportunities for Reductions). 

31 U.S Greenhouse Gas Emissions and Sinks: 1990-2003. 

32 The assumption that 59 percent of landfills recovering CH 4 will use it for energy is subject to change over time 
based upon changes in the cost of recovery and the potential payback. Additionally, new technologies may be 
developed that use recovered CH 4 for purposes other than generating electricity and direct gas use. 


87 












textbooks—also have the highest gross CH 4 generation, as shown in column “b.” The recovery of CH 4 at 
landfills reduces the CH 4 emissions for each material in proportionate amounts but does not change the 
ranking of materials by CH 4 emissions. Grass, leaves, branches, and the two wood products have the 
lowest rates of net GHG emissions from CH 4 generation. 

6.3 UTILITY C0 2 EMISSIONS AVOIDED 

Exhibit 6-7 presents a list of conversion factors and physical constants used to convert CH 4 
combusted for electricity production to avoided C0 2 emissions. Using data on Btu per cubic feet of CfL, 
kWh of electricity generated and delivered per Btu, and kilograms of utility carbon avoided per Btu 
delivered, EPA estimated that 0.15 MTCE is avoided per MTCE of CH 4 combusted. This figure then was 
incorporated into Exhibit 6-8 to estimate net GHG emissions from landfills with electricity generation. 

As mentioned earlier in this chapter, the analysis assumes that 31 percent of CH 4 generated in the United 
States comes from landfills that combust landfill CH 4 for electricity generation. EPA also assumes a 15 
percent system efficiency loss, reflecting the fact that landfill gas-to-energy facilities incur some system 
“down-time,” as shown in column 1. Landfill CH 4 is assumed to be flared during down-time periods. 

6.4 NET GHG EMISSIONS FROM LANDFILLING 

To determine the net GHG emissions from landfilling each material, the net GHG emissions from 
CH 4 generation, carbon storage (treated as negative emissions), and transportation C0 2 emissions were 
summed. The results are shown in Exhibit 6-8. The four columns under section “e” of the exhibit may be 
used by local MSW planners to estimate GHG emissions from MSW in a given community. 

As the exhibit shows, the postconsumer results for organic materials vary widely. For some 
materials—in particular newspaper and phonebooks—landfilling results in substantial negative net GHG 
emissions. For others—including office paper, textbooks, and food discards—net emissions are 
significant. For the rest, net emissions and reductions are relatively small. 


88 


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6.5 LIMITATIONS 

Perhaps the most important caveat to the analysis of GHG emissions and storage associated with 
landfilling is that the results are based on a single set of laboratory experiments, those conducted by Dr. 
Morton Barlaz. Although researchers other than Dr. Barlaz have conducted laboratory studies that track 
the degradation of mixed MSW, his experiments were the only ones EPA identified that rigorously tested 
materials on an individual basis. Dr. Barlaz is recognized as an expert on the degradation of different 
fractions of MSW under anaerobic conditions, and his findings with respect to the CH 4 potential of mixed 
MSW are within the range used by landfill gas developers. Nevertheless, given the sensitivity of the 
landfill results to estimated CH 4 generation and carbon storage, EPA recognizes that more research is 
needed in this area. 

Another important caveat relates to the estimate that 59 percent of MSW landfill CH 4 is generated 
at landfills with LFG recovery systems. The net GHG emissions from landfilling each material are quite 
sensitive to the LFG recovery rate. Because of the high GWP of CH 4 , small changes in the LFG recovery 
rate (for the national average landfill) could have a large effect on the net GHG impacts of landfilling 
each material and the ranking of landfilling relative to other MSW management options. The effects of 
different rates of LFG recovery are shown in Exhibit 6-9. Column “b” of the exhibit shows net GHG 
emissions if 20 percent of waste were disposed of at landfills with recovery. The remaining columns 
show net GHG emissions at increasing LFG recovery rates, up to a 60 percent rate. As the exhibit shows, 
the net postconsumer GHG emissions for landfilling mixed MSW decline significantly as recovery 
increases. At the local level, the GHG emissions from landfilling MSW depend on whether the local 
landfill has LFG recovery, as shown in Exhibit 6-8. 

Because the national average estimate of emissions is based on estimated year 2003 LFG 
recovery levels, several limitations are associated with the use of this emission factor. First, because 
landfill CH 4 generation occurs over time and has significant timing delays (i.e., CH 4 generation may not 
begin until a few years after the waste is deposited in the landfill and can continue for many years after 
the landfill is closed), the values listed in this chapter represent total CH 4 generated, over time, per ton of 
waste landfilled. To the extent that LFG recovery rates shift dramatically over time, these shifts are not 
reflected in the analysis. Second, landfills with LFG recovery may be permitted, under EPA regulations, 
to remove the LFG recovery equipment when three conditions are met: (1) the landfill is permanently 
closed, (2) LFG has been collected continuously for at least 15 years, and (3) the landfill emits less than 
50 metric tons of non-CH 4 organic compounds per year. 33 Although the removal of LFG recovery 
equipment will permit CH 4 from closed landfills to escape into the atmosphere, the amounts of CH 4 
emitted should be relatively small, because of the length of time required for LFG collection before LFG 
recovery equipment is removed. Third, several methodological issues are associated with applying the 
CH 4 generation estimates from the Inventory ofU.S. Greenhouse Gas Emissions and Sinks (U.S. 
Inventory) to develop the national average emission factors: 34 

(1) The generation estimates in the U.S. Inventory include closed landfills (generation is modeled as 
a function of waste in place), whereas the estimates used in this report apply to ongoing 
generation (which is routed to open landfills); 

(2) Likewise, both the flaring and landfill gas-to-energy estimates also include closed landfills; and 

(3) The distribution of waste in place is not a perfect proxy for the destination of ongoing waste 
generation. 


33 Federal Register, 1996, Vol. 61, No. 49, p. 9907. 

34 U.S. Department of State, 2002. U.S. Climate Action Report — 2002. Washington DC, May. 


90 



CH 4 oxidation rate and landfill gas collection system efficiency are also important factors driving 
results. EPA used values of 10 percent and 75 percent, respectively, as best estimates for these factors. 
Reviewers of previous editions of this report and sources in the literature have reported estimates ranging 
from about 5 percent to 40 percent for oxidation, and from about 60 to 95 percent for collection system 
efficiency. EPA investigated the sensitivity of the results to these assumptions, and the results are shown 
in Exhibit 6-10. To portray the sensitivity as a bounding analysis, EPA used the combinations of 
variables yielding the upper bound emission factor (5 percent oxidation, 60 percent collection efficiency) 
and the lower bound (40 percent oxidation, 95 percent efficiency). 35 As the exhibit shows, the materials 
most sensitive to these variables are those with the highest CH 4 generation potential, i.e., corrugated 
cardboard, office paper, textbooks, food discards, and mixed paper. Sensitivity varies: the difference 
between upper and lower bounds ranges from 0.05 MTCE/ton for grass to 0.42 MTCE/ton for office 
paper and textbooks. The postconsumer emission factors of several materials and mixed material 
combinations—corrugated cardboard, grass, mixed paper, and mixed MSW—change from having net 
storage under the lower bound to having net emissions under the upper bound. 

Ongoing shifts in the use of landfill cover and liner systems are likely to influence the rate of CH 4 
generation and collection. As more landfills install effective covers and implement controls to keep water 
and other liquids out, conditions will be less favorable for degradation of organic wastes. Over the long 
term, these improvements may result in a decrease in CH 4 generation and an increase in carbon storage. 
Moreover, Dr. Barlaz believes that the CH 4 yields from his laboratory experiments are likely to be higher 
than CH 4 yields in a landfill, because the laboratory experiments were designed to generate the maximum 
amount of CH 4 possible. If the CH 4 yields from the laboratory experiments were higher than yields in a 
landfill, the net GHG emissions from landfilling organic materials would be lower than estimated here. 

EPA assumed that once wastes are disposed in a landfill, they are never removed. In other words, 
it was assumed that landfills are never “mined.” A number of communities have mined their landfills— 
removing and combusting the waste—in order to create more space for continued disposal of waste in the 
landfill. To the extent that landfills are mined in the future, it is incorrect to assume that carbon stored in 
a landfill will remain stored. For example, if landfilled wastes are later combusted, the carbon that was 
stored in the landfill will be oxidized to C0 2 in the combustor. 

The estimate of avoided utility GHG emissions per unit of CH 4 combusted assumes that all 
landfill gas-to-energy projects are electricity producing. In reality, some projects are “direct gas” 
projects, in which CH 4 is piped directly to the end user for use as fuel. In these cases, the CH 4 typically 
replaces natural gas as a fuel source. Because natural gas use is less GHG-intensive than average 
electricity production, direct gas projects will tend to offset fewer GHG emissions than electricity projects 
will—a fact not reflected in the analysis. 

For landfilling of yard trimmings (and other organic materials), EPA assumed that all carbon 
storage in a landfill environment is incremental to the storage that occurs in a nonlandfill environment. In 
other words, it was assumed that in a baseline where yard trimmings are returned to the soil (i.e., in a 
nonlandfill environment), all of the carbon is decomposed relatively rapidly (i.e., within several years) to 
CO : , and there is no long-term carbon storage. To the extent that long-term carbon storage occurs in the 
baseline, the estimates of carbon storage reported here are overstated, and the net postconsumer GHG 
emissions are understated. 


35 Exhibit 6-10 also reports two intermediate combinations, including the best estimate values. 


91 



Finally, the analysis is limited by the assumptions that were made at various steps in the analysis, 
as described throughout this chapter. The key assumptions that have not already been discussed as 
limitations are the assumptions used in developing “corrected” CH4 yields for organic materials in MSW. 
Because of the high GWP of CH 4 , a small difference between estimated and actual CH 4 generation values 
would have a large effect on the GHG impacts of landfilling and the ranking of landfilling relative to 
other MSW management options. 


Exhibit 6-7 

Calculation to Estimate Utility GHGs Avoided through Combustion of 
_ Landfill CH 4 _ 


Step 

Value 

Source 

Metric tons 

ch 4 /mtce ch 4 

0.17 

1/((12/44) x Global warming potential 
of CH 4 ) 

Grams CH 4 /metric ton 

ch 4 

1.00E+06 

Physical constant 

Cubic ft. CH 4 /gram 

ch 4 

0.05 

1/20: 20 grams per cubic foot of CH 4 at 
standard temperature and pressure 

Btu/cubic ft. CH 4 

1,012 

EPA 2005. LMOP Benefits Calculator. 

kWh electricity 
generated/Btu 

0.00009 

1/11,700: EPA 2005. LMOP Benefits 
Calculator. 

Electricity generation 
efficiency 

0.85 

EPA 2005. LMOP Net capacity factor 
for generation units (availability, 
operating load, parasitic losses). 

Kg utility C 
avoided/kWh 
generated electricity 

2.405E-01 

0.24 kg CE/kWh generated electricity, 
from Exhibit 5-4. This assumes that 

LFG energy recovery displaces fossil 
fuel generation. 

Metric tons avoided 
utility C/kg utility C 

0.001 

1000 kg per metric ton 

Ratio of MTCE 
avoided utility C per 
MTCECH 4 ‘ 

0.15 

Product from multiplying all factors 


92 














Exhibit 6-8 

Net GHG Emissions from Landfilling 


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Exhibit 6-9 


Net GHG Emissions from CH 4 Generation at Landfills with Recovery (MTCE/Wet Ton) 


Sensitivity Analysis 

: Varying the Percentage of Waste Disposed at Landfills with CH 4 

Recovery 

(a) 

(b) 

(c) 

(d) 

(e) 

(f) 

Material 

17% 

20% 

49% 

55% 

60% 

Corrugated Cardboard 

0.32 

0.30 

0.15 

0.12 

0.09 

Magazines/Third-class Mail 

0.00 

0.00 

-0.07 

-0.08 

-0.09 

Newspaper 

-0.16 

-0.17 

-0.22 

-0.23 

-0.24 

Office Paper 

0.89 

0.86 

0.60 

0.54 

0.50 

Phonebooks 

-0.16 

-0.17 

-0.22 

-0.23 

-0.24 

Textbooks 

0.89 

0.86 

0.60 

0.54 

0.50 

Dimensional Lumber 

-0.03 

-0.03 

-0.11 

-0.13 

-0.14 

Medium-density Fiberboard 

-0.03 

-0.03 

-0.11 

-0.13 

-0.14 

Food Discards 

0.33 

0.32 

0.22 

0.20 

0.19 

Yard Trimmings 

0.02 

0.01 

-0.04 

-0.06 

-0.07 

Grass 

0.04 

0.04 

0.01 

0.00 

-0.01 

Leaves 

0.04 

0.03 

-0.03 

-0.05 

-0.06 

Branches 

-0.03 

-0.03 

-0.11 

-0.13 

-0.14 

Mixed Paper 3 






Broad Definition 

0.29 

0.28 

0.13 

0.10 

0.08 

Residential Definition 

0.25 

0.24 

0.10 

0.08 

0.05 

Office Paper Definition 

0.32 

0.31 

0.16 

0.13 

0.11 

Mixed MSW 

0.29 

0.28 

0.15 

0.12 

0.10 


The summary values for mixed paper are based on the proportions of the four paper types (corrugated cardboard, magazines/third- 
class mail, newspaper, and office paper) that constitute the different "mixed paper" definitions. 


94 










Exhibit 6-10 


Net GHG Emissions from CH 4 Generation at Landfills with Recovery (MTCE/Wet Ton) 


Sensitivity Analysis: Varying Oxidation 

and Gas Collection Efficiency Rates. 

Oxidation Rate: 

40% 

25% 

10% 

5% 

Collection Efficiency: 

95% 

85% 

75% 

60% 


Lower- 

Conservative 



Material 

bound 

Emissions 

(High) 

Emissions 

Best 

Estimate 

Upper-bound 

Emissions 

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0.18 

0.26 

0.34 

0.42 

Magazines/Third-class Mail 

0.07 

0.10 

0.14 

0.17 

Newspaper 

0.06 

0.09 

0.12 

0.15 

Office Paper 

0.31 

0.45 

0.60 

0.73 

Phonebooks 

0.06 

0.09 

0.12 

0.15 

Textbooks 

0.31 

0.45 

0.60 

0.73 

Dimensional Lumber 

0.09 

0.13 

0.18 

0.22 

Medium-density Fiberboard 

0.09 

0.13 

0.18 

0.22 

Food Discards 

0.12 

0.17 

0.22 

0.27 

Yard Trimmings 

0.07 

0.10 

0.13 

0.16 

Grass 

0.04 

0.06 

0.08 

0.09 

Leaves 

0.07 

0.10 

0.14 

0.17 

Branches 

0.09 

0.13 

0.18 

0.22 

Mixed Paper a 





Broad Definition 

0.17 

0.24 

0.33 

0.40 

Residential Definition 

0.16 

0.23 

0.31 

0.38 

Office Paper Definition 

0.17 

0.24 

0.32 

0.39 

Mixed MSW 

0.15 

0.22 

0.29 

0.36 


a The summary values for mixed paper are based on the proportions of the four paper types (corrugated cardboard, 
magazines/third-class mail, newspaper, and office paper) that constitute the different "mixed paper" definitions. 


95 











This page intentionally left blank. 


96 


7. ENERGY IMPACTS 


The previous chapters of this report were focused on life-cycle GHG emissions associated with 
each of five management options for MSW. Materials have energy impacts at each life-cycle stage; the 
stages addressed in this report include the acquisition of raw materials, the manufacture of raw materials 
into products, and product disposal or recovery. Waste reduction practices (source reduction, recycling, 
and reuse) reduce the demand for raw material and energy inputs to the manufacturing stage of the life 
cycle, thereby conserving energy and reducing GHG emissions. Energy savings can also result from 
some waste disposal practices, including waste-to-energy combustors and landfill gas-to-energy systems. 

To better understand the relationship between materials management and energy use, energy 
factors were developed for four waste management practices (source reduction, recycling, combustion, 
and landfilling), and this chapter includes a discussion on how to use these energy factors and the 
relationship between energy savings and GHG benefits. 

7.1 METHODOLOGY FOR DEVELOPING ENERGY FACTORS 

The methodology used to develop these emission factors is fundamentally the same as described 
in the preceding chapters, except that here the researchers view all life-cycle components through the lens 
of energy consumption or savings, rather than GHG emissions. Components such as forest carbon 
sequestration and landfill carbon storage are not a part of the energy life cycle; therefore they are not 
described here. The energy factors are based primarily on the amount of energy required to produce 1 ton 
of a given material. The total energy consumed is a result of direct fossil fuel and electricity consumption 
associated with raw material acquisition and manufacturing; fossil fuel consumption for transportation; 
and embedded energy. The total process and transportation energy for the production of both virgin and 
recycled materials is shown in Exhibits 2-3 to 2-7. Although the GHG emission factors are a product of 
fuel mix and the carbon coefficients of fuels, the energy factors are based only on the energy consumption 
(direct fossil fuel and electricity) component and are left in terms of Btu of energy consumption. 
Therefore, the total process energy required to make 1 ton of a particular material is the sum of energy 
consumed across all of the fuel types. 

The total energy, or embodied energy, required to manufacture each material is made up of two 
components: (1) process and transportation energy, and (2) embedded energy (i.e., energy of the raw 
material). The process and transportation components are conceptually straightforward, but embedded 
energy is more complex. Embedded energy is the energy contained within the raw materials used to 
manufacture a product. For example, the embedded energy of plastics is due to their being made from 
petroleum. Because petroleum has an inherent energy value, the amount of energy that is saved through 
plastic recycling and source reduction is directly related to the energy that could have been produced if 
the petroleum had been used as an energy source rather than as a raw material input. Aluminum is the 
other material in this analysis that includes an embedded energy component. The aluminum smelting 
process requires a carbon anode, which is consumed during the electrolytic reduction process; carbon 
anodes are made from coal, itself an energy source. Total energy values contained in this report also 
include both nonrenewable and renewable sources. For example, the total energy savings estimate for 
recycling paper includes some renewable energy fuel sources that may have little oi no associated GHG 

emissions. 


97 




7.2 ENERGY IMPLICATIONS FOR WASTE MANAGEMENT OPTIONS 

This chapter presents the life-cycle energy implications for four waste management practices. As 
with the GHG emission factors already presented, negative values indicate net energy savings. 

Waste reduction efforts such as source reduction and recycling can result in significant energy 
savings. Source reduction techniques such as double-sided copying and light-weighting are in most cases 
more effective at reducing energy than recycling. This is because source reduction significantly reduces 
energy consumption associated with raw material extraction and manufacturing processes. 

When comparing recycling to landfill disposal, aluminum cans give the greatest energy savings 
per ton, as shown in Exhibit 7-1. These savings reflect the nature of aluminum production; 
manufacturing aluminum cans from virgin inputs is very energy intensive, whereas relatively little energy 
is required to manufacture cans from recycled aluminum. Recycling carpet also results in significant 
energy savings, since the recycled material is turned into secondary products and the energy-intensive 
processes that would have been used to manufacture those secondary products are avoided. 

Exhibit 7-1 Energy Savings per Ton Recycled a 


Aggregate 
Textbooks 
Magazines/third class mail 

Glass 
Fly Ash 
Office Paper 
Phonebooks 
Corrugated Cardboard 
Newspaper 
Steel Cans 
Personal Computers 
HDPE 
PET 
LDPE 
Copper Wire 
Carpet 
Aluminum Cans 



Million Btu/ton 


3 Assumes recycled materials would otherwise have been landfilled. Aggregate refers to concrete recycled as aggregate. 

Some materials, such as dimensional lumber and medium-density fiberboard, actually use more 
energy when they are made from recycled inputs. For these materials, the recovery and processing of 
recycled material is more energy intensive than making the material from virgin inputs. Although these 
materials may not provide an energy benefit from recycling, from a GHG emissions perspective, 
recycling these materials is still beneficial. Exhibit 7-2 presents the GHG benefits attributable to the 
energy savings achieved through recycling. 


98 



Exhibit 7-2 Recycling GHG Benefits Attributable to Energy Savings (Recycling vs. Landfilling) 



7.3 APPLYING ENERGY FACTORS 

Due to recent fuel shortages and increases in prices for fuel and energy, it is becoming 
increasingly important to examine the impacts of waste management practices on energy. The energy 
factors presented in Exhibit 7-3 through Exhibit 7-8 may be used by organizations interested in 
quantifying energy savings associated with waste management practices. With these exhibits, 
organizations can compare the energy benefits of switching from landfilling to one of the other waste 
management options. For example, using these factors, the researchers evaluated the progress of 
voluntary programs aimed at source reduction and recycling, such as EPA’s WasteWise, Pay-as-You- 
Throw, and Coal Combustion Product Partnership (C : P 2 ) programs. 

In order to apply the energy factors presented in this report, one must first establish two 
scenarios: (1) a baseline scenario that represents current management practices (e.g., disposing of 1 ton of 
steel cans in a landfill); and (2) an alternative scenario that represents the alternative management practice 
(e.g., recycling the same ton of steel cans). 1 The energy factors developed in this report can then be used 
to calculate energy consumed or avoided under both the baseline and the alternative management 
practices. Once energy for the two scenarios has been determined, the next step is to calculate the 
difference between the alternative scenario and the baseline scenario. The result represents the energy 
consumed or avoided that is attributable to the alternative waste management practice. 

Exhibit 7-8 illustrates the application of these factors where the baseline management scenario is 
disposal in a landfill with national average conditions. In the alternate scenario, the material is recycled. 
For example, recycling 1 ton of steel cans rather than landfilling them reduces the energy consumed by 
20.5 million Btu. The calculations used to generate this result are shown below. Under the sign 
convention used in this report, the negative value indicates that energy consumption is avoided. 

Energy Impacts of Waste Reduction 

Baseline: landfill 1 ton of steel cans 
1 ton x 0.53 million Btu/ton = 0.53 million Btu 

Alternate: recycle 1 ton of steel cans 
1 ton x -19.97 million Btu/ton = -19.97 million Btu 

Energy Savings: 

-19.97 million Btu - 0.53 million Btu = 

- 20.5 million Btu 


1 The energy factors are expressed in terms of million Btu of energy per ton of material managed. In the case of 

recycling, EPA defines 1 ton of material managed as 1 ton collected for recycling. 


99 



























































In cases where parties have been source reducing or recycling materials not specifically 
analyzed in this report, it is possible to estimate the energy consumed or avoided by assigning surrogate 
materials. A list of materials not specifically analyzed and their corresponding surrogates is presented in 
the following chapter. Surrogates are based on similarities in characteristics likely to drive energy 
factors, such as similarities in energy consumption during the raw material acquisition and manufacturing 
life-cycle stages. Note that the use of these surrogates involves considerable uncertainty. 

7.4 RELATING ENERGY SAVINGS TO GHG BENEFITS 

It can be difficult to conceptualize energy savings in Btu and GHG emissions reductions in 
MTCE; therefore, these quantities are frequently converted to common equivalents such as barrels of 
crude oil or gallons of gasoline. There are important nuances to inteipreting these equivalencies, 
particularly converting from savings in MTCE to equivalent energy savings. This is complicated for two 
reasons: (1) GHG reductions reflect both energy and nonenergy savings, and (2) the energy savings 
reflect savings across a range of fossil fuels. Thus, converting from total GHG reductions to an 
equivalency for “barrels of oil” must be done with caution. 


Common Energy Conversion Factors 

Fuel: Million Btu per Barrel of Oil: 5.8 

Gallons Oil per Barrel of Oil: 42 
Million Btu per Gallon of Gas: 0.125 

Cars (“average” passenger car over one year): Fuel Consumption (gallons of gas): 502 

C0 2 Emissions (tons): 4.6 


Although energy savings are often the driving force behind GHG emissions savings, it would not 
be accurate to directly convert overall GHG emission benefits into energy savings equivalents. 
Equivalencies must remain consistent within the energy or GHG emission context in which they were 
originally created. As shown in Exhibit 7-2, energy consumption can account for only a fraction of the 
emission benefits associated with some material types. For example, only about 55 percent of the 
emission benefits for recycling glass are due to energy consumption. Because the GHG benefits of glass 
recycling consist of some energy and some nonenergy-related savings, this material type demonstrates the 
difficulties of converting GHG savings to energy equivalents. When the total GHG benefits of recycling 
glass are converted to barrels of oil using the common equivalency factors, the GHG emission benefits are 
equivalent to GHG emissions from the combustion of 68 barrels of oil. In contrast, the energy savings 
associated with recycling glass are equivalent to the energy content of 46 barrels of oil. 

Recycling 100 tons of Glass Compared to Landfilling 
GHG Emission Benefits: 9 MTCE 
Equivalent to the combustion emissions from 68 barrels of oil. 

Energy Savings: 265 Million Btu 
Equivalent to the energy contained within 46 barrels of oil. 

Understanding the differences between these values is very important. Similarly, because energy 
savings estimates are based on a diverse fuel mix of fuels (electricity, natural gas, petroleum, coal, etc.), 
the results do not mean that 46 barrels of oil will be avoided in the real world. The equivalency “barrels 
of oil” is simply utilized as a recognizable and understandable unit of energy. In the case of 
manufacturing glass, the primary energy sources are electricity, coal, and natural gas with only a small 
fraction of the total energy derived from petroleum products. 


100 













Exhibit 7-3 

Energy Consumed/Avoided for Source Reduction (Million Btu/Ton of Material Source Reduced) 


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Exhibit 7-4 

Energy Consumed/Avoided for Recycling (Million Btu/Ton of Material Recycled) 


Material 

(a) 

Recycled Input Credit 
Process Energy 

(b) 

Recycled Input Credit 
Transportation Energy 

(C) 

Net 

Consumption/Savings 

(Postconsumer) 

Aluminum Cans 

-200.68 

-5.74 

-206.42 

Steel Cans 

-19.40 

-0.56 

-19.97 

Copper Wire 

-81.64 

-0.95 

-82.59 

Glass 

-1.91 

-0.21 

-2.13 

HDPE 

-50.97 

0.06 

-50.90 

LDPE 

-56.07 

0.06 

-56.01 

PET 

-52.90 

0.06 

-52.83 

Corrugated Cardboard 

-14.67 

-0.74 

-15.42 

Magazines/Third-class Mail 

-0.69 

0.00 

-0.69 

Newspaper 

-16.07 

-0.42 

-16.49 

Office Paper 

-10.08 

0.00 

-10.08 

Phonebooks 

-11.93 

0.51 

-11.42 

Textbooks 

-1.03 

0.50 

-0.53 

Dimensional Lumber 

0.52 

0.07 

0.59 

Medium-density Fiberboard 

0.65 

0.21 

0.86 

Food Discards 

NA 

0.58 

0.58 

Yard Trimmings 

NA 

0.58 

0.58 

Mixed Paper 




Broad Definition 

-21.38 

-1.57 

-22.94 

Residential Definition 

-21.38 

-1.57 

-22.94 

Office Paper Definition 

-12.98 

-0.97 

-13.95 

Mixed Metal 

-72.72 

-2.08 

-74.81 

Mixed Plastics 

-52.48 

0.06 

-52.42 

Mixed Recyclables 

-16.36 

-0.55 

-16.91 

Mixed Organics 

NA 

0.58 

0.58 

Mixed MSW (as disposed) 

NA 

NA 

NA 

Carpet 

-103.67 

-1.90 

-105.58 

Personal Computers 

-41.95 

-1.48 

-43.44 

Clay Bricks 

NA 

NA 

NA 

Concrete 

-0.01 

-0.09 

-0.11 

Fly Ash 

-4.77 

0.00 

-4.77 

Tires 3 

-51.96 

0.00 

-51.96 


a Recycling of tires, as modeled in this analysis, consists only of retreading the tires. 


102 










Exhibit 7-5 


Energy Consumed/Avoided 

or Combustion i 

Million Btu/Ton of Material Combusted) 



Energy 

Savings 


Net 


Avoided Utility 

Due to 

Transportation to 

Consumption/ 


Fuel 

Steel 

Combustion 

Savings 

Material 

Consumption 

Recovery 

Facility 

(Postconsumer) 

Aluminum Cans 

0.12 

NA 

0.30 

0.42 

Steel Cans 

0.07 

-17.61 

0.30 

-17.24 

Copper Wire 

0.10 

NA 

0.30 

0.39 

Glass 

0.08 

NA 

0.30 

0.38 

HDPE 

-6.66 

NA 

0.30 

-6.37 

LDPE 

-6.66 

NA 

0.30 

-6.37 

PET 

-3.46 

NA 

0.30 

-3.16 

Corrugated Cardboard 

-2.51 

NA 

0.30 

-2.21 

Magazines/Third-class Mail 

-1.87 

NA 

0.30 

-1.58 

Newspaper 

-2.83 

NA 

0.30 

-2.54 

Office Paper 

-2.42 

NA 

0.30 

-2.13 

Phonebooks 

-2.83 

NA 

0.30 

-2.54 

Textbooks 

-2.42 

NA 

0.30 

-2.13 

Dimensional Lumber 

-2.96 

NA 

0.30 

-2.66 

Medium-density Fiberboard 

-2.96 

NA 

0.30 

-2.66 

Food Discards 

-0.85 

NA 

0.30 

-0.55 

Yard Trimmings 

-1.00 

NA 

0.30 

-0.70 

Mixed Paper 





Broad Definition 

-2.52 

NA 

0.30 

-2.22 

Residential Definition 

-2.51 

NA 

0.30 

-2.21 

Office Paper Definition 

-2.32 

NA 

0.30 

-2.02 

Mixed Metals 

0.09 

-12.43 

0.30 

-12.05 

Mixed Plastics 

-5.39 

NA 

0.30 

-5.09 

Mixed Recyclables 

-2.36 

-0.61 

0.30 

-2.67 

Mixed Organics 

-0.88 

NA 

0.30 

-0.58 

Mixed MSW (as disposed) 

-1.78 

NA 

0.30 

-1.49 

Carpet 

-4.78 

NA 

0.30 

-4.78 

Personal Computers 

-0.55 

-4.44 

0.30 

-4.69 

Clay Bricks 

NA 

NA 

NA 

NA 

Concrete 

NA 

NA 

NA 

NA 

Fly Ash 

NA 

NA 

NA 

NA 

Tires 

-25.95 

-1.06 

0.30 

-26.71 


103 


















Exhibit 7-6 


Energy Consumed/Avoided for Landfilling (Million B 

tu/Ton of Material Landfilled) 

Material 

Transportation to 
Landfill 

Avoided Utility 
Energy 

Net Consumption/ 
Savings 

(Postconsumer) 

Aluminum Cans 

0.53 

NA 

0.53 

Steel Cans 

0.53 

NA 

0.53 

Copper Wire 

0.53 

NA 

0.53 

Glass 

0.53 

NA 

0.53 

HDPE 

0.53 

NA 

0.53 

LDPE 

0.53 

NA 

0.53 

PET 

0.53 

NA 

0.53 

Corrugated Cardboard 

0.53 

(0.30) 

0.23 

Magazines/Third-class Mail 

0.53 

(0.12) 

0.41 

Newspaper 

0.53 

(0.11) 

0.42 

Office Paper 

0.53 

(0.52) 

0.01 

Phonebooks 

0.53 

(0.11) 

0.42 

Textbooks 

0.53 

(0.52) 

0.01 

Dimensional Lumber 

0.53 

(0.15) 

0.37 

Medium-density Fiberboard 

0.53 

(0.15) 

0.37 

Food Discards 

0.53 

(0.19) 

0.33 

Yard Trimmings 

0.53 

(0.11) 

0.41 

Mixed Paper 

Broad Definition 

0.53 

(0.28) 

0.24 

Residential Definition 

0.53 

(0.27) 

0.26 

Office Paper Definition 

0.53 

(0.28) 

0.25 

Mixed Metals 

0.53 

NA 

0.53 

Mixed Plastics 

0.53 

NA 

0.53 

Mixed Recyclables 

0.53 

(0.22) 

0.30 

Mixed Organics 

0.53 

(0.15) 

0.37 

Mixed MSW (as disposed) 

0.53 

(0.25) 

0.28 

Carpet 

0.53 

NA 

0.53 

Personal Computers 

0.53 

NA 

0.53 

Clay Bricks 

0.53 

NA 

0.53 

Concrete 

0.53 

NA 

0.53 

Fly Ash 

0.53 

NA 

0.53 

Tires 

0.53 

NA 

0.53 


104 













Exhibit 7-7 

Net Energy Consumed/Avoided from Source Reduction and MSW Management Options 
__ (Million Btu/Ton) __ 


Material 

Source Reduction 

Recycling 

Combustion 

Landfilling 

Aluminum Cans 

-126.18 

-206.42 

0.42 

0.53 

Steel Cans 

-30.79 

-19.97 

-17.24 

0.53 

Copper Wire 

-122.31 

-82.59 

0.39 

0.53 

Glass 

-7.53 

-2.13 

0.38 

0.53 

HDPE 

-63.68 

-50.90 

-6.37 

0.53 

LDPE 

-73.92 

-56.01 

-6.37 

0.53 

PET 

-70.67 

-52.83 

-3.16 

0.53 

Corrugated Cardboard 

-21.91 

-15.42 

-2.21 

0.23 

Magazines/Third-class Mail 

-33.21 

-0.69 

-1.58 

0.41 

Newspaper 

-36.45 

-16.49 

-2.54 

0.42 

Office Paper 

-36.58 

-10.08 

-2.13 

0.01 

Phonebooks 

-39.87 

-11.42 

-2.54 

0.42 

Textbooks 

-35.30 

-0.53 

-2.13 

0.01 

Dimensional Lumber 

-3.53 

0.59 

-2.66 

0.37 

Medium-density Fiberboard 

-11.51 

0.86 

-2.66 

0.37 

Food Discards 

NA 

0.58 

-0.55 

0.33 

Yard Trimmings 

NA 

0.58 

-0.70 

0.41 

Mixed Paper 





Broad Definition 

NA 

-22.94 

-2.22 

0.24 

Residential Definition 

NA 

-22.94 

-2.21 

0.26 

Office Paper Definition 

NA 

-13.95 

-2.02 

0.25 

Mixed Metals 

NA 

-74.81 

-12.05 

0.53 

Mixed Plastics 

NA 

-52.42 

-5.09 

0.53 

Mixed Recyclables 

NA 

-16.91 

-2.67 

0.30 

Mixed Organics 

NA 

0.58 

-0.58 

0.37 

Mixed MSW (as disposed) 

NA 

NA 

-1.49 

0.28 

Carpet 

-91.06 

-105.58 

-4.78 

0.53 

Personal Computers 

-956.74 

-43.44 

-4.69 

0.53 

Clay Bricks 

-5.13 

NA 

NA 

0.53 

Concrete 

NA 

-0.11 

NA 

0.53 

Fly Ash 

NA 

-4.77 

NA 

0.53 

Tires 

-88.17 

-51.96 3 

-26.71 

0.53 


a Recycling of tires, as modeled in this analysis, consists only of retreading the tires. 


105 











Exhibit 7-8 

Energy Consumed/Avoided for MSW Management Options Compared to Landfilling 


Material 

Source Reduction 
Net Energy Minus 
Landfilling Net 
Energy (Current Mix) 

Source Reduction 
Net Energy Minus 
Landfilling Net 
Energy (100% Virgin 
Inputs) 

Recycling Net 
Energy Minus 
Landfilling Net 
Energy 

Combustion Net 
Energy Minus 
Landfilling Net 
Energy 

Aluminum Cans 

-126.71 

-239.41 

-206.95 

-0.11 

Steel Cans 

-31.32 

-37.02 

-20.49 

-17.77 

Copper Wire 

-122.84 

-123.82 

-83.12 

-0.13 

Glass 

-8.06 

-8.62 

-2.65 

-0.15 

HDPE 

-64.21 

-70.76 

-51.43 

-6.89 

LDPE 

-74.45 

-77.33 

-56.54 

-6.89 

PET 

-71.20 

-73.24 

-53.36 

-3.69 

Corrugated Cardboard 

-22.13 

-26.99 

-15.65 

-2.44 

Magazines/Third-class Mail 

-33.62 

-33.66 

-1.09 

-1.98 

Newspaper 

-36.87 

-41.10 

-16.91 

-2.96 

Office Paper 

-36.59 

-37.28 

-10.09 

-2.14 

Phonebooks 

-40.29 

-40.29 

-11.84 

-2.96 

Textbooks 

-35.31 

-35.34 

-0.54 

-2.14 

Dimensional Lumber 

-3.90 

-3.90 

0.21 

-3.04 

Medium-density Fiberboard 

-11.88 

-11.88 

0.49 

-3.04 

Food Discards 

NA 

NA 

0.25 

-0.88 

Yard Trimmings 

NA 

NA 

0.17. 

-1.11 

Mixed Paper 





Broad Definition 

NA 

NA 

-23.19 

-2.47 

Residential Definition 

NA 

NA 

-23.20 

-2.47 

Office Paper Definition 

NA 

NA 

-14.20 

-2.27 

Mixed Metals 

NA 

NA 

-75.33 

-12.57 

Mixed Plastics 

NA 

NA 

-52.94 

-5.62 

Mixed Recyclables 

NA 

NA 

-17.21 

-2.97 

Mixed Organics 

NA 

NA 

0.21 

-0.93 

Mixed MSW (as disposed) 

NA 

NA 

-0.28 

-1.76 

Carpet 

-91.59 

-91.59 

-106.11 

-5.31 

Personal Computers 

-957.27 

-957.27 

-43.96 

-5.22 

Clay Bricks 

-5.66 

-5.66 

NA 

NA 

Concrete 

NA 

NA 

-0.63 

NA 

Fly Ash 

NA 

NA 

-5.29 

NA 

Tires 

-88.70 

-88.70 

-52.49 a 

-27.23 


1 Recycling of tires, as modeled in this analysis, consists only of retreading the tires. 


106 











8. ENERGY AND EMISSION BENEFITS 


Earlier chapters of this report examined the energy implications and GHG emissions from each of 
five waste management options. This chapter summarizes the GHG emission factors for each option, 
explains the analytic framework for applying emission factors, reviews tools that can be used to evaluate 
GHG emissions from waste management practices, and describes opportunities for GHG emission 
reductions. The full discussion of the energy implications of waste management options, and tables 
showing the associated energy savings, are presented in Chapter 7. Readers are referred to Chapter 7 for 
complete explanation of energy impacts, or for help applying energy factors to a particular waste 
management option. 

In the discussion that follows, the focus is on national average conditions. For example, landfills 
are represented as having the national average landfill gas recovery systems, and combustors are 
represented based on mass bum units with the national average system efficiency for collection of ferrous 
metal. As shown in the previous chapters, GHG emissions are sensitive to site-specific variables; 
emissions can and do differ from the national average scenario presented here. To allow customization of 
emission factors that better reflect site-specific conditions, EPA has developed three accounting tools: the 
WAste Reduction Model (WARM), which enables users to input several key variables (e.g., information 
on landfill gas collection systems, transportation distances) to assess the GHG and energy implications of 
waste management options; the Recycled Content (ReCon) Tool, which enables consumers and producers 
to assess the energy and GHG impacts of buying or producing goods with varying percentages of 
recycled content; and the Durable Goods Calculator, which assesses the energy and GHG impacts of 
recycling goods such as refrigerators and washing machines. EPA encourages readers to take advantage 
of these models when assessing their waste management options. The tools are described in further detail 
in Section 8.3 below. 

8.1 NET GHG EMISSIONS FOR EACH WASTE MANAGEMENT OPTION 

The net life-cycle GHG emissions for each waste management option for each material 
considered are shown in 8 exhibits that summarize the GHG emissions and sinks in MTCE/ton, which are 
described in detail in earlier chapters. In these exhibits, emission factors are shown for mixed plastics, 
mixed recyclables, and mixed organics. EPA developed the emission factor for mixed recyclables by 
calculating the average (weighted by tons recycled in 2003) of emission factors for aluminum cans, steel 
cans, glass, HDPE, LDPE, PET, corrugated cardboard, magazines/third-class mail, newspaper, office 
paper, phonebooks, textbooks, medium-density fiberboard, and dimensional lumber. The emission factor 
for mixed plastics is the average (weighted by tons recycled in 2003) of emission factors for HDPE, 
LDPE, and PET. The mixed organics emission factor is the average (weighted by tons composted in 
2003) of emission factors for yard trimmings and food discards. 1 

As mentioned in Chapter 1, EPA used a waste generation reference point for measuring GHG 
emissions (i.e., GHG emissions were accounted for at the point of waste generation). All subsequent 
emissions and sinks from waste management practices are counted. Changes in emissions and sinks from 
raw material acquisition and manufacturing processes are captuied to the extent that source i eduction and 
recycling affect these processes. 2 Negative emission factors indicate that, from a waste generation 


1 All data on recycling and compost rates are from EPA’s OSW. 2005. Municipal Solid Waste in the United States: 
2003 Facts and Figures , EPA 430-R-05-003. 

2 For reference, GHG emissions from raw materials acquisition and manufacturing are shown in column “a” of 
several exhibits in this chapter. 


107 






reference point, a given management practice for a particular material type results in emission reductions. 
However, it is important to note that none of the management-specific emission factors are to be used 
alone; it is the difference between two competing management practices that matters. 

This report provides emissions and savings from several of the most common materials in MSW. 
For materials not explicitly covered in the previous chapters, Exhibit 8-1 presents the recommended 
proxy materials that readers of this report can use to calculate emissions of common materials not covered 
in the body of the report, including mixed metals, PVC, rubber, and textiles. 


Exhibit 8-1 Recommended Surrogates for Voluntary Reporting 


Material Source Reduced 

Surrogate Material 

Iron 

Steel Cans 

Other Ferrous Metals 

Steel Cans 

Other Nonferrous Metals 

Average of Copper and Aluminum 

Steel 

Steel Cans 

Metal (type unknown) 

Average of Aluminum, Steel, and Copper 

Mixed Metals (ferrous and nonferrous) 

Appropriate Weighted Average 

Copper 

Copper Wire 

Plastic (resin unknown) 

Average of PET, HDPE, and LDPE 

PVC/Vinyl 

Average of PET, HDPE, and LDPE 

Polypropylene 

Average of PET, HDPE, and LDPE 

Polystyrene 

Average of PET, HDPE, and LDPE 

Other plastic (resin known, but not 41-46) 

Average of PET, HDPE, and LDPE 

Rubber 

Average of PET, HDPE, and LDPE 

Boxboard 

Corrugated Cardboard 

Kraft Paper 

Corrugated Cardboard 

Coated Paper 

Magazines/Third-class Mail 

High-grade Paper 

Office Paper 

Paper (type unknown) 

Mixed Paper - Broad Definition 

Wood 

Dimensional Lumber 

Food 

Food Discards 

Organics (type unknown) 

Yard Trimmings 

Other Yard Waste 

Yard Trimmings 

Textiles 

Carpet 


Exhibit 8-2 shows the life-cycle GHG impacts of source reduction, presented in MTCE/ton. 3 In 
brief, the exhibit shows that, for all of the manufactured materials evaluated, source reduction results in 
GHG emission reductions. On a per-ton basis, PCs, aluminum cans, and copper wire have the greatest 
potential for emission reduction, due primarily to reductions in energy use in the raw material acquisition 
and manufacturing step. 

Exhibit 8-3 shows the life-cycle GHG emissions associated with recycling. Columns (c), (d), and 
(e) show the GHG impacts of using recycled inputs in place of virgin inputs when the material is 
remanufactured. As the final column indicates, recycling results in negative emissions (measured from 
the point of waste generation) for all the materials considered in this analysis. GHG emission reductions 
associated with recycling are due to several factors, including avoided waste management emissions and 
reduced process energy emissions. 4 In addition, emission reductions from recycling paper products 


3 All data in these tables are presented in metric tons of carbon equivalent per short ton of waste discarded 
(MTCE/ton). To see these tables in MTC0 2 E/ton, please refer to Appendix B. 

4 Process energy emissions for recycled corrugated cardboard, office paper, wood products (i.e., dimensional lumber 
and medium-density fiberboard), and mixed paper (broad and residential definitions) are actually higher than those 
for virgin production because production with recycled inputs tends to use fossil fuel-derived energy, while 
production with virgin inputs uses higher proportions of biomass fuel (C0 2 from such fuel is not counted in GHG 


108 





(when measured at the point of waste generation) are due in part to the forest carbon sequestration 
benefits ot recycling paper. The materials with the greatest potential for emission reduction through 
recycling are aluminum cans, carpet, copper wire, and several paper grades. In addition, though the 
emission reductions per ton for concrete are relatively small (0.002), the enormous quantities of this 
material disposed ot make it particularly promising as a mitigation strategy—200 million tons of waste 
concrete are disposed of annually in the United States. 

Exhibit 8-4 presents the life-cycle GHG emissions from composting food discards, yard 
trimmings, and mixed organics. The exhibits show that composting these materials results in net 
emissions ot -0.05 MTCE/ton, based on the difference between the emissions associated with transporting 
the materials to the composting facility and the soil carbon sequestration benefits. 

Exhibit 8-5 presents the life-cycle GHG emissions from combusting each of the materials 
considered. This exhibit shows emissions for mass bum facilities and assumes the national average rate 
of ferrous recovery. Results for RDF facilities are similar. As the exhibit shows, mixed MSW 
combustion has net emissions of-0.03 MTCE/ton. Net GHG emissions are positive for plastics, 
aluminum, and glass, and negative for the other materials. 

GHG emissions from landfilling each of the materials in MTCE/ton are shown in Exhibit 8-6. 

The values in the final column indicate that net GHG emissions from landfilling mixed MSW, under 
national average conditions in 2003, are positive. Among individual materials, emissions are lowest for 
newspaper, phonebooks, magazines/third-class mail, wood products, and yard trimmings, and highest for 
office paper, textbooks, and food discards. 

As discussed in Chapter 6 and shown in Exhibit 6-6, the results for landfills are very sensitive to 
site-specific factors. Landfill gas collection practices significantly influence the net GHG emissions from 
landfilling the organic materials. For mixed MSW, net emissions are 0.37 MTCE/ton in landfills without 
landfill gas collection, and -0.09 MTCE/ton in landfills with landfill gas collection and energy recovery 
(see Exhibit 6-8), a difference of 0.46 MTCE to be gained by recovering and using landfill gas for 
electricity generation. The largest such differences attributable to landfill gas recovery are for office 
paper and textbooks (approximately 0.8 MTCE/ton), corrugated cardboard and mixed paper. The CFf 
oxidation rate and gas collection system efficiency also have a strong influence on the estimated net 
emissions for mixed waste and the organic materials. The values in Exhibit 8-6 reflect national average 
CH 4 recovery practices, thus the value for mixed MSW is 0.12 MTCE/ton. 

Exhibit 8-7 displays the national average emissions for each management option and each 
material in MTCE/ton. When reviewing the emission factors, it is important to recall caveats that appear 
throughout this report. In particular, these estimates do not reflect site-specific variability, and they are 
not intended to compare one material to another from a use-phase perspective. Rather, these estimates are 
designed to support accounting for GHG emissions and sinks from waste management practices. A brief 
recap of how to apply the emission factors appears in the following section. 

8.2 APPLYING GHG EMISSION FACTORS 

The net GHG emission estimates presented in Exhibit 8-2 through Exhibit 8-7 (and the more 
detailed estimates in the preceding chapters) provide emission factors that may be used by organizations 
interested in quantifying and voluntarily reporting emissions reductions associated with waste 
management practices. In conjunction with DOE, EPA has used these estimates as the basis tor 
developing guidance for voluntary reporting of GHG reductions, as authorized by Congress in Section 
1605(b) of the Energy Policy Act of 1992. However, under the new, more rigorous 1605(b) reporting 
guidelines, emissions reductions from solid waste management practices must be reported separately 


inventories). In the case of dimensional lumber, production with recycled inputs requires more energy than virgin 
production. 


109 





Applying Emission Factors: Nonlinear Relationship between Recycling and Emission Reductions and 

Forest Carbon Leakage 

Two caveats should be considered when applying emission factors to analyze large-scale shifts in waste 
management. First, increased recycling and GHG emission reductions may have a nonlinear relationship, such 
that emission reductions increase at a declining rate as recycling increases. This decline may be due to three 
factors: (1) energy use in manufacturing processes may be nonlinear with respect to recycled content; (2) 
manufacturing capacity for recycled materials may be limited in the short term, so that large-scale increases in 
recycling would require additional capital investment in capacity; and (3) market penetration of recyclables may 
have limits (e.g., due to performance characteristics), such that recyclables cannot completely replace virgin 
inputs in the short term. 

In terms of the second caveat, the forest carbon sequestration benefits of paper and wood source 
reduction and recycling are based on the assumption that reduced demand for a given paper or wood product 
translates directly into reduced tree harvesting. Given that pulpwood and roundwood can be used for many 
products, some of the forest carbon sequestration benefits may be lost by an increase in harvests for these other 
products. This phenomenon is a form of what is sometimes termed “leakage” in the context of GHG mitigation 
projects. 

Although both of these issues are important considerations in applying the emission factors in this report, 
EPA notes that the emission factors are primarily designed for use by local waste managers. The factors are 
intended to assess the GHG impacts of waste management decisions at a small-to-moderate scale. Readers should 
be cautious when applying the emission factors at a larger scale, however, since the nonlinear nature of the 
factors and the issue of leakage become most relevant in the larger context. 


tons of office paper). '' The emission factors developed in this report then can be used to calculate 
emissions under both the baseline and the alternative management practices. Once emissions for the two 
scenarios have been determined, the next step is to calculate the difference between the alternative 
scenario and the baseline scenario. The result represents the GHG emission reductions or increases 
attributable to the alternative waste management practice. 

Exhibit 8-8 illustrates the results of this procedure in a scenario where the baseline management 
scenario is disposal in a landfill with national average conditions (i.e., the weighted average in terms of 
landfill gas recovery practice). Alternative scenarios involve source reduction, recycling, composting, or 
combustion. The values in the cells of the matrix are expressed in MTCE/ton and represent the 
incremental change in GHG emissions. For example, recycling 1 ton of office paper, rather than 
landfilling it, reduces GHG emissions by 1.31 MTCE, (see the “Recycling” columns of the exhibit). 
Continuing the example from the previous paragraph, if a business implements an office paper recycling 
program and annually diverts 10 tons of office paper (that would otherwise be landfilled) to recycling, the 
GHG emission reductions are: 

10 tons/yr x -1.31 MTCE/ton = -13.1 MTCE/yr 

Under the sign convention used in this report, the negative value indicates that emissions are 
reduced. 

In 2003, the most recent year for which data was available, the United States recycled 30.6 
percent of the MSW it produced. As part of its effort to encourage recycling, waste reduction, and GHG 
reduction, the EPA has set national recycling goal of 35 percent by 2008 and has proposed a goal of 40 
percent by 2011. Using WARM, EPA calculated the projected incremental benefits of these goals. The 
current rate of 30.6 percent gave GHG benefits in 2003 of 49 MMTCE and energy benefits of 1.5 

5 The emission factors are expressed in terms of GHG emissions per ton of material managed. In the case of 
recycling, EPA defines 1 ton of material managed as 1 ton collected for recycling. As discussed in Chapter 4, the 
emission factors can be adjusted to calculate GHG emissions in terms of tons of recycled materials as marketed 
(reflecting losses in collection and sorting processes), or changes in the recycled content of products. 


110 








quadrillion Btu saved compared to a baseline of no recycling. These calculations assume landfilling 80 
percent and combusting 20 percent of MSW not recycled (the national average rates). Increasing the rate 
to 35 percent would give GHG benefits in 2008 of 57 MMTCE and energy benefits of 1.7 quadrillion Btu 
saved. The benefits in 2011 of a 40 percent recycling rate would be 65 MMTCE and 1.9 quadrillion Btu. 

Due to resource and data limitations, emission factors have not been developed for all material 
types reported by WasteWise partners, the Voluntary Reporting of GHG Program—or 1605(b) as it is 
commonly called—and other parties interested in reporting voluntary emission reductions. However, 
existing emission factors will continue to be updated and improved and new emission factors will be 
developed as more data become available. The latest emission factors, reflecting these ongoing revisions, 
can be found in WARM, EPA’s waste emissions spreadsheet tool. 6 7 

In cases where parties have been using source reduction or recycling techniques for materials 
not specifically analyzed in this report, it is possible to estimate the GHG emission reductions by 
assigning surrogate materials. A list of materials not specifically analyzed, and their corresponding 
surrogates, is presented earlier in this chapter (see Exhibit 8-1). Surrogates are assigned based on 
consideration of similarities in characteristics likely to drive life-cycle GHG emissions, such as 
similarities in energy consumption during the raw material acquisition and manufacturing life-cycle 
stages. Note that the use of these surrogates involves considerable uncertainty. 

8.3 TOOLS AND OTHER LIFE-CYCLE GHG ANALYSES 

Life-cycle analysis is increasingly being used to quantify the GHG impacts of private and public 
sector decisions. In addition to the life-cycle analyses that underpin the emission factors in this report, 
Environmental Defense, ICLEI, Ecobilan, and others have analyzed the life-cycle environmental impacts 
of various industry processes (e.g., manufacturing) and private and public sector practices (e.g., waste 
management). In many cases, the results of life-cycle analyses are packaged into life-cycle software tools 
that distill the information according to a specific user’s needs. 

ICF International worked with EPA to create the WARM, ReCon, and DGC tools, in addition to 
researching and writing this report, and creating the emission factors used here and in the tools. As 
mentioned earlier, the WAste Reduction Model (WARM) was designed as a tool for waste managers to 
weigh the GHG and energy impacts of their waste management practices. As a result, the model focuses 
exclusively on waste sector GHG emissions, and the methodology used to estimate emissions is 
consistent with international and domestic GHG accounting guidelines. Life-cycle tools designed for 
broader audiences necessarily include other sectors and/or other environmental impacts, and are not 
necessarily tied to the IPCC guidelines for GHG accounting or the methods used in the Inventory ofU.S. 
Greenhouse Gas Emissions and Sinks. 

• WARM covers 34 types of materials and five waste management options: source reduction, 
recycling, combustion, composting, and landfilling. WARM accounts for upstream energy and 
nonenergy emissions, transportation distances to disposal and recycling facilities, carbon 
sequestration, and utility offsets that result from landfill gas collection and combustion. The tool 
provides participants in DOE’s 1605(b) program with the option to report results by year, by gas, 
and by year and by gas (although under 1605(b)’s revised guidelines, avoided emissions from 
recycling must be reported separately under “other indirect emissions” and not included in the 


6 Available at EPA’s Global Warming—Waste, “Waste Reduction Model” website. Available at: 
http://www.epa.gov/mswclimate. then follow the link to Tools. 

7 Blum. L„ Denison, R.A., and Ruston, V.F. 1997. “A Life-Cycle Approach to Purchasing and Using 
Environmentally Preferable Paper: A Summary of the Paper Task Force Report, Journal of Industi ial Ecology , 
Volume 1; No. 3; pp, 15-46. Denison, R.A. 1996. “Environmental Life-Cycle Comparison of Recycling, 
Landfilling, and Incineration: A Review of Recent Studies;” Annual Review of Energy and the Environment; 
Volume 21, Chapter 6, pp. 191-23 7. 


Ill 





main corporate inventory). WARM software is available free of charge in both a Web-based 
calculator format and a Microsoft® Excel spreadsheet. The tool is ideal for waste planners 
interested in tracking and reporting voluntary GHG emission reductions from waste management 
practices and comparing the climate change impacts of different approaches. To access the tool, 
visit: http://www.epa.gov/mswclimate , and follow the link to Tools. The latest version ot 
WARM can also calculate energy savings resulting from waste management decisions. 

• Recycled Content (ReCon) Tool was created by EPA to help companies and individuals estimate 
life-cycle GHG emissions and energy impacts from purchasing and/or manufacturing materials with 
varying degrees of postconsumer recycled content. The tool covers 17 material types and an 
analysis of baseline and alternative recycled-content scenarios. ReCon accounts for total 
“upstream” GHG emissions based on manufacturing processes, carbon sequestration, and avoided 
disposal that are related to the manufacture of the materials with recycled content. ReCon also 
accounts for the total energy (based on manufacturing processes and avoided disposal) related to the 
manufacture of materials with recycled content. The tool is ideal for companies and individuals 
who want to calculate GHG emissions and energy consumption associated with purchasing and 
manufacturing, using baseline and alternate recycled-content scenarios. To access the tool, visit: 
http://www.epa.gov/mswclimate, and follow the link to Tools. 

• The Durable Goods Calculator (DGC) is an EPA model that enables users to calculate the GHG 
emission and energy implications for various disposal methods of durable goods. The model 
covers 14 types of durable goods and three waste management options: recycling, landfilling, and 
combustion. This tool functions by producing an aggregate GHG emission profile by creating a 
weighted average of the raw material content. The Durable Goods Calculator was developed for 
individuals and companies who want to make an informed decision on the GHG and energy 
impact they will have by disposing of durable household goods. Emission and energy estimates 
provided by the Durable Goods Calculator are intended to provide information regarding the 
GHG emission implications of waste management decisions. To access the tool, visit: 
http://www.epa.gov/mswclimate, and follow the link to Tools. 

• The Cities for Climate Protection (CCP) campaign’s GHG Emission Software was developed by 
Torrie Smith Associates for ICLEI (Local Governments for Sustainability). This Windows™- 
based tool, targeted for use by local governments, can analyze emissions and emission reductions 
on a community-wide basis and for municipal operations alone. The community-wide module 
looks at residential, commercial, and industrial buildings, transportation activity, and community¬ 
generated waste. The municipal operations module considers municipal buildings, municipal 
fleets, and waste from municipal in-house operations. In addition to computing GHG emissions, 
the CCP software estimates reductions in criteria air pollutants, changes in energy consumption, 
and financial costs and savings associated with energy use and other emission reduction 
initiatives. A version of the software program was made available for use by private businesses 
and institutions during the summer of 2001. CCP software subscriptions, including technical 
support, are available to governments participating in ICLEI. For more information, visit: 
www.iclei.org or contact the U.S. ICLEI office at 510-844-0699, iclei_usa@iclei.org. 

• The Decision Support Tool (DST) and life-cycle inventory database for North America have been 
developed through funding by EPA’s ORD through a cooperative agreement with the Research 
Triangle Institute (CR823052). The methodology is based on a multimedia, multipollutant 
approach and includes analysis of GHG emissions as well as a broader set of emissions (air, 
water, and waste) associated with MSW operations. The MSW-DST is available for site-specific 
applications and has been used to conduct analyses in several states and 15 communities, 
including use by the U.S. Navy in the Pacific Northwest. The tool is intended for use by solid 
waste planners at state and local levels to analyze and compare alternative MSW management 


112 



strategies with respect to cost, energy consumption, and environmental releases to the air, land, 
and water. The costs are based on full-cost accounting principles and account for capital and 
operating costs using an engineering economics analysis. The MSW-DST calculates not only 
projected emissions of GHGs and criteria air pollutants, but also emissions of more than 30 air- 
and water-borne pollutants. The DST models emissions associated with all MSW management 
activities, including waste collection and transportation, transfer stations, materials recovery 
facilities, compost facilities, landfills, combustion and refuse-derived fuel facilities, utility offsets, 
material offsets, and source reduction. The differences in residential, multifamily, and 
commercial sectors can be evaluated individually. The software has optimization capabilities that 
enable one to identify options that evaluate minimum costs as well as solutions that can maximize 
environmental benefits, including energy conservation and GHG reductions. 

As of the publication of this report, RTI expects to release the database in the summer of 2006, 
and will be available in a Web-based version. The MSW-DST provides extensive default data for 
the full range of MSW process models and requires minimum input data. The defaults can be 
tailored to the specific communities using site-specific information. The MSW-DST also 
includes a calculator for source reduction and carbon sequestration using a methodology that is 
consistent with the IPCC in terms of the treatment of biogenic CCF emissions. For further 
information, visit RTFs website at http://www.rti.org/ , and search the term “DST.” 

• The Tool for Environmental Analysis and Management (TEAM), developed by Ecobilan, 
simulates operations associated with product design, processes, and activities associated with 
several industrial sectors. The model considers energy consumption, material consumption, 
transportation, waste management, and other factors in its evaluation of environmental impacts. 
Many firms and some government agencies have used the model. 
http://www.ecobalance.com/uk_team.php. 

8.4 OPPORTUNITIES FOR GHG REDUCTIONS 

Although this report has focused on the five most common waste management practices—source 
reduction, recycling, composting, combustion, and landfilling—for select materials, future GHG 
quantification efforts may include a number of emerging practices: 

• Co-firing waste biomass . For utilities and power generating companies with coal-fired capacity, 
co-firing with waste biomass may represent one of the least-cost renewable energy options. Co¬ 
firing involves replacing a portion of the coal with biomass at an existing power plant boiler. 

This replacement can be achieved by either mixing biomass with coal before fuel is introduced 
into the boiler or by using separate fuel feeds for coal and biomass. Specific biomass feedstocks 
include agricultural and wood waste, MSW, and industrial wastes. Given the increasing use of 
co-firing technology as an energy source, understanding its GHG benefits will likely be an 
important future EPA effort. 

• Biomass pyrolvsis/gasification . Pyrolysis and gasification are similar technologies in which 
waste is thermally decomposed in an oxygen-poor environment. In pyrolysis, organic matter is 
vaporized, and the vapor is condensed and collected as “bio-oil,” which can then be burned for 
energy. 8 The advantage of pyrolysis over normal waste-to-energy incineration is that pyrolysis 
produces a liquid fuel that can be stored and used in a number of applications (similar to 
biodiesel), whereas WTE produces only electricity for immediate consumption. Biomass 
gasification is similar except that a gas rather than a liquid is produced. 


8 The Biomass Technology Group, “Flash Pyrolysis.” Available online at: 

www.btgworld.coin/technologies/pvrolysis.htm l. 


113 








• Compost as landfill cover . Using compost as landfill cover on closed landfills provides an 
excellent environment for the bacteria that oxidize CH 4 . Under optimal conditions, compost 
covers can practically eliminate CH 4 emissions. Furthermore, the covers offer the possibility of 
controlling these emissions in a cost-effective manner. This technology is particularly promising 
for small landfills, where landfill gas collection is not required and the economics of landfill gas- 
to-energy projects are not attractive. Ancillary benefits also might arise in the compost market 
from this technique if using compost as a landfill cover becomes a widespread practice. An 
increase in composting could reduce the quantity of organic waste disposed of at MSW landfills, 
thereby reducing CH 4 emissions. Given the recent development of this practice, quantifying its 
GHG impacts will likely prove useful as landfill owners consider adopting the technology. 

• Bioreactors . Bioreactors are a form of controlled landfilling with the potential to provide reliable 
energy generation from solid waste, as well as significant environmental and solid waste 
management benefits. The concept is to accelerate the decomposition process of landfill waste 
through controlled additions of liquid and leachate recirculation, which enhances the growth of 
the microbes responsible for solid waste decomposition. The result is to shorten the period of 
landfill gas generation, thereby rendering projections of landfill gas generation rates and yields 
that are much more reliable for landfill gas recovery. 

• Anaerobic digestion. Several facilities are using this technique to produce CH 4 from mixed 
waste, which is then used to fuel energy recovery. The approach generates CH 4 more quickly and 
captures it more completely than in a landfill environment, and thus, from a GHG perspective, 
offers a potentially attractive waste management option. 4 

• The paperless office . The rise of computer technology for research, communications, and other 
everyday workplace functions has presented a major opportunity for source reduction in the 
modem office. Today’s offices are commonly equipped with all the necessary technologies to 
bypass paper entirely and rely instead on electronic communication. This form of 
“comprehensive” source reduction comes with significant GHG benefits, as described in Chapter 
4. Therefore, attempting to quantify and communicate these benefits to the business community 
will be an important task in the coming years. 

• Product stewardship . More and more companies, and even entire industries, are moving toward 
redesigning their products to reduce their environmental footprint. By necessity, this trend 
involves rethinking how their products are managed at end-of-life so that valuable materials can 
be recovered and reused. The electronics industry is reducing the energy usage of their products 
as well as reducing reliance on toxic inputs in their products. They are also redesigning their 
products to make them easier to recycle. The packaging industry is moving towards package 
designs that use less material (reducing GHG emissions from transportation) and are more easily 
recyclable (reducing GHG emissions and energy investments in processing virgin materials). 
Many other industries, such as the carpet, office furniture, and textile industries, are in the process 
of developing sustainability standards for their products. Companies committed to this kind of 
change are very interested in metrics that will help them measure the environmental benefits of 
the changes they are making to their products. 

EPA will continue to evaluate new opportunities to reduce emissions from waste management as 
they become known. EPA also encourages readers to consider creative approaches to waste management, 
particularly those with associated life-cycle energy benefits or carbon storage implications. All of the 
exhibits presented so far in this report have expressed GHG emissions in units of MTCE, calculated as the 
sum of the individual gases (C0 2 , CH 4 , N 2 0, and PFCs) weighted by their global warming potential. In 


4 Environment Canada. 2001. Determination of the Impact of Waste Management Activities on Greenhouse Gas 
Emissions. Submitted by ICF Consulting, Torrie-Smith Associates, and Enviros-RIS. 


114 








the Voluntary Reporting of GHG Program—also known as the 1605(b) program—established by DOE’s 
Energy Information Administration, reporting companies are asked to provide emission reductions for 
each of the individual gases. In addition, the 1605(b) program requires emission reductions to be reported 
in the year they are achieved and does not allow participants to take credit for future emission reductions. 
Because the GHG emission factors presented in this report reflect the “present value” of future emissions 
and sinks as well as emissions and sinks occurring in the reporting year, these emission factors are not 
directly transferable to the 1605(b) program. For purposes of supporting the program, EPA developed a 
revised set of 1605(b) program emission factors that reflect emissions by gas and by year. Those 
emission factors provide incremental emissions for a baseline of landfilling and alternative scenarios of 
source reduction and recycling, although as noted above, savings calculated in this manner can no longer 
be directly counted under the revised 1605(b) reporting guidelines. Detailed reporting instructions and 
forms are available on DOE’s website at: 

http://www.pi.energy.gov/enhancingGHGregistry/generalguidelines.html. 


115 



Exhibit 8-2 

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a Material that is recycled after use is then substituted for virgin inputs in the production of new products. This credit represents the difference in emissions that results from using recycled inputs. 
a Recycling of tires, as modeled in this analysis, consists only of retreading the tires. 


















Exhibit 8-4 

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a The value for mixed MSW is the weighted average of the RMAM emissions for those materials EPA studied. 










Exhibit 8-5 

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Values are for Mass Burn Facilities with National Average Rate of Ferrous Recovery. 


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Exhibit 8-6 

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a Values for landfill CH 4 and net emissions reflect projected national average CH4 recovery in year 2004. 
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Exhibit 8-7 

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A final note about the limitations of the GHG emission and energy consumption estimates 
presented in this report. EPA based its analysis on what was believed to be the best available data; where 
necessary, reasonable assumptions were made. The accuracy of the estimates is limited, however, by the 
use of these assumptions and limitations in the data sources, as discussed throughout this report. Where 
possible, the emission and energy factors reported here can be improved by substituting process- or site- 
specific data to increase the accuracy of the estimates. For example, a commercial firm with a large 
aluminum recycling program may have better data on the specific fuel mix of its source of aluminum and 
could thus calculate a more exact value for the emission factor. Despite the uncertainty in the emission 
and energy factors, they provide a reasonable first approximation of the GHG and energy impacts of solid 
waste management, and EPA believes that they provide a sound basis for evaluating voluntary actions to 
reduce GHG emissions and energy consumption in the waste management arena. 


123 


This page intentionally left blank. 


124 


APPENDIX A: GHG EMISSIONS FROM A RAW MATERIALS EXTRACTION 

VIEWPOINT. 

The analyses conducted in the main body of this report are based on a life-cycle perspective that starts at 
the moment a material is discarded. EPA took this approach because expert review of the first edition 
indicated that the “waste-generation” approach would be more useful and comprehensible to waste 
managers, at whom this report is chiefly aimed. This is in contrast to a typical life-cycle analysis, which 
takes a “cradle-to-grave” approach. Emission factors from raw materials extraction and manufacturing 
perspective are presented here for those who find this viewpoint more useful. 


Exhibit A-1 

Net GHG Emissions from Source Reduction and MSW Management Options - Emissions 
_ Counted from a Raw Materials Extraction Reference Point (MTCE/Ton) _ 


Material 

Source 

Reduction 3 

Recycling 13 

Composting 13 

Combustion 6 

Landfilling 6 

Aluminum Cans 

0.00 

-1.46 

NA 

2.26 

2.26 

Steel Cans 

0.00 

0.38 

NA 

0.45 

0.88 

Copper Wire 

0.00 

0.66 

NA 

2.02 

2.01 

Glass 

0.00 

0.08 

NA 

0.17 

0.17 

HDPE 

0.00 

0.11 

NA 

0.74 

0.50 

LDPE 

0.00 

0.16 

NA 

0.87 

0.63 

PET 

0.00 

0.15 

NA 

0.87 

0.58 

Corrugated Cardboard 

-1.29 

-0.61 

NA 

0.06 

0.34 

Magazines/Third-class Mail 

-1.90 

-0.38 

NA 

0.33 

0.38 

Newspaper 

-0.80 

-0.24 

NA 

0.32 

0.29 

Office Paper 

-1.90 

-0.49 

NA 

0.11 

0.81 

Phonebooks 

-1.04 

-0.04 

NA 

0.48 

0.44 

Textbooks 

-1.90 

-0.25 

NA 

0.43 

1.13 

Dimensional Lumber 

-0.50 

-0.62 

NA 

-0.16 

-0.08 

Medium-density Fiberboard 

-0.50 

-0.57 

NA 

-0.11 

-0.03 

Food Discards 

NA 

NA 

-0.05 

-0.05 

0.20 

Yard Trimmings 

NA 

NA 

-0.05 

-0.06 

-0.06 

Mixed Paper 

Broad Definition 

NA 

-0.67 

NA 

0.11 

0.39 

Residential Definition 

NA 

-0.68 

NA 

0.11 

0.36 

Office Paper Definition 

NA 

-0.05 

NA 

0.72 

1.01 

Mixed Metals 

NA 

-0.16 

NA 

0.98 

1.29 

Mixed Plastics 

NA 

0.13 

NA 

0.81 

0.55 

Mixed Recyclables 

NA 

-0.41 

NA 

0.22 

0.42 

Mixed Organics 

NA 

NA 

-0.05 

-0.05 

0.06 

Mixed MSW as Disposed 

NA 

NA 

NA 

-0.03 

0.12 

Carpet 

0.00 

-0.87 

NA 

1.20 

1.10 

Personal Computers 

0.00 

14.51 

NA 

15.07 

15.14 

Clay Bricks 

0.00 

0.08 

NA 

0.08 

0.09 

Concrete 

NA 

0.00 

NA 

NA 

0.01 

Fly Ash 

Tires 

NA 

-0.24 

NA 

NA 

0.01 

0.00 

2.07 c 

NA 

3.86 

3.82 


Note that totals may not add due to rounding, and more digits may be displayed than are significant. 


NA: Not applicable, or in the case of composting of paper, not analyzed. 

a Source reduction assumes initial production using the current mix of virgin and recycled inputs. 

'includes emissions from the initial production of the material being managed, except for foodwaste, yard waste, and 

mixed MSW. 


c Recycling of tires, as modeled in this analysis, consists only of retreading the tires 


125 









Exhibit A-2 

Net GHG Emissions from Source Reduction and MSW Management Options - Emissions 
Counted from a Raw Materials Extraction Reference Point (MTC0 2 E/Ton) _ 


Material 

Source 

Reduction 3 

Recycling 6 

Composting 6 

Combustion 6 

Landfilling 6 

Aluminum Cans 

0.00 

-5.34 

NA 

8.29 

8.27 

Steel Cans 

0.00 

1.38 

NA 

1.64 

3.21 

Copper Wire 

0.00 

2.42 

NA 

7.39 

7.38 

Glass 

0.00 

0.29 

NA 

0.62 

0.61 

HDPE 

0.00 

0.39 

NA 

2.72 

1.82 

LDPE 

0.00 

0.57 

NA 

3.20 

2.31 

PET 

0.00 

0.56 

NA 

3.18 

2.13 

Corrugated Cardboard 

-4.73 

-2.25 

NA 

0.21 

1.26 

Magazines/Third-class Mail 

-6.96 

-1.38 

NA 

1.22 

1.39 

Newspaper 

-2.95 

-0.87 

NA 

1.18 

1.06 

Office Paper 

-6.96 

-1.81 

NA 

0.41 

2.98 

Phonebooks 

-3.83 

-0.16 

NA 

1.75 

1.62 

Textbooks 

-6.96 

-0.90 

NA 

1.58 

4.15 

Dimensional Lumber 

-1.84 

-2.28 

NA 

-0.60 

-0.31 

Medium-density Fiberboard 

-1.84 

-2.10 

NA 

-0.40 

-0.11 

Food Discards 

NA 

NA 

-0.20 

-0.18 

0.72 

Yard Trimmings 

Mixed Paper 

NA 

NA 

-0.20 

-0.22 

-0.22 

Broad Definition 

NA 

-2.47 

NA 

0.41 

1.41 

Residential Definition 

NA 

-2.48 

NA 

0.41 

1.31 

Office Paper Definition 

NA 

-0.17 

NA 

2.65 

3.71 

Mixed Metals 

NA 

-0.60 

NA 

3.60 

4.70 

Mixed Plastics 

NA 

0.48 

NA 

2.97 

2.02 

Mixed Recyclables 

NA 

-1.52 

NA 

0.79 

1.54 

Mixed Organics 

NA 

NA 

-0.20 

-0.20 

0.24 

Mixed MSW as Disposed 

NA 

NA 

NA 

-0.12 

0.42 

Carpet 

0.00 

-3.19 

NA 

4.38 

4.03 

Personal Computers 

0.00 

53.21 

NA 

55.27 

55.51 

Clay Bricks 

0.00 

0.28 

NA 

0.28 

0.32 

Concrete 

NA 

-0.01 

NA 

NA 

0.04 

Fly Ash 

NA 

-0.87 

NA 

NA 

0.04 

Tires 

0.00 

7.57 c 

NA 

14.15 

14.01 


Note that totals may not add due to rounding, and more digits may be displayed than are significant. 

NA: Not applicable, or in the case of composting of paper, not analyzed. 

a Source reduction assumes initial production using the current mix of virgin and recycled inputs. 

includes emissions from the initial production of the material being managed, except for foodwaste, yard waste, and 

mixed MSW. 

c Recycling of tires, as modeled in this analysis, consists only of retreading the tires. 


126 










APPENDIX B: CARBON DIOXIDE EQUIVALENT EMISSION FACTORS 


Exhibit B-1 

Net GHG Emissions from Source Reduction and MSW Management Options - Emissions 
Counted from a Waste Generation Reference Point (MTC0 2 E/Ton) a 



Source 





Material 

Reduction 13 

Recycling 

Composting" 

Combustion d 

Landfilling 6 

Aluminum Cans 

-8.23 

-13.57 

NA 

0.06 

0.04 

Steel Cans 

-3.18 

-1.79 

NA 

-1.53 

0.04 

Copper Wire 

-7.34 

-4.92 

NA 

0.05 

0.04 

Glass 

-0.57 

-0.28 

NA 

0.05 

0.04 

HDPE 

-1.79 

-1.39 

NA 

0.93 

0.04 

LDPE 

-2.27 

-1.69 

NA 

0.93 

0.04 

PET 

-2.09 

-1.54 

NA 

1.08 

0.04 

Corrugated Cardboard 

-5.59 

-3.11 

NA 

-0.65 

0.40 

Magazines/Third-class Mail 

-8.65 

-3.07 

NA 

-0.47 

-0.30 

Newspaper 

-4.87 

-2.79 

NA 

-0.74 

-0.87 

Office Paper 

-8.00 

-2.85 

NA 

-0.62 

1.94 

Phonebooks 

-6.32 

-2.66 

NA 

-0.74 

-0.87 

Textbooks 

-9.17 

-3.11 

NA 

-0.62 

1.94 

Dimensional Lumber 

-2.02 

-2.46 

NA 

-0.78 

-0.49 

Medium-density Fiberboard 

-2.22 

-2.47 

NA 

-0.78 

-0.49 

Food Discards 

NA 

NA 

-0.20 

-0.18 

0.72 

Yard Trimmings 

NA 

NA 

-0.20 

-0.22 

-0.22 

Mixed Paper 






Broad Definition 

NA 

-3.54 

NA 

-0.65 

0.35 

Residential Definition 

NA 

-3.54 

NA 

-0.65 

0.25 

Office Paper Definition 

NA 

-3.42 

NA 

-0.59 

0.47 

Mixed Metals 

NA 

-5.25 

NA 

-1.06 

0.04 

Mixed Plastics 

NA 

-1.49 

NA 

0.99 

0.04 

Mixed Recyclables 

NA 

-2.91 

NA 

-0.61 

0.14 

Mixed Organics 

NA 

NA 

-0.20 

-0.20 

0.24 

Mixed MSW as Disposed 

NA 

NA 

NA 

-0.12 

0.42 

Carpet 

-3.99 

-7.18 

NA 

0.39 

0.04 

Personal Computers 

-55.47 

-2.26 

NA 

-0.20 

0.04 

Clay Bricks 

-0.28 

NA 

NA 

NA 

0.04 

Concrete 

NA 

-0.01 

NA 

NA 

0.04 

Fly Ash 

NA 

-0.87 

NA 

NA 

0.04 

Tires 

-3.98 

-1.82 f 

NA 

0.18 

0.04 


Note that totals may not add due to rounding, and more digits may be displayed than are significant. 


NA: Not applicable, or in the case of composting of paper, not analyzed. 

a MTCE/ton: Metric tons of carbon equivalent per short ton of material. Material tonnages are on an as-managed (wet 
weight) basis. 

"Source reduction assumes initial production using the current mix of virgin and recycled inputs. 
c There is considerable uncertainty in our estimate of net GHG emissions from composting; 

The values of zero are plausible values based on assumptions and a bounding analysis. 

"Values are for mass burn facilities with national average rate of ferrous recovery. 

'Values reflect estimated national average methane recovery in year 2004. 

'Recycling of tires, as modeled in this analysis, consists only of retreading the tires. 


127 













Exhibit B-2 

GHG Emissions of MSW Management Options Compared to Landfilling 3 (MTC0 2 E/Ton) 
(Management Option Net Emissions Minus Landfilling Net Emissions) 


Material 

Source 

Reduction 5 

(Current 

Mix) 

Source 

Reduction 

(100% 

Virgin 

Inputs) 

Recycling 

Composting 0 

Combustion 5 

Aluminum Cans 

-8.27 

-15.68 

-13.61 

NA 

0.02 

Steel Cans 

-3.21 

-3.73 

-1.83 

NA 

-1.57 

Copper Wire 

-7.38 

-7.44 

-4.96 

NA 

0.02 

Glass 

-0.61 

-0.68 

-0.32 

NA 

0.01 

HDPE 

-1.82 

-2.00 

-1.43 

NA 

0.89 

LDPE 

-2.31 

-2.39 

-1.73 

NA 

0.89 

PET 

-2.13 

-2.19 

-1.58 

NA 

1.04 

Corrugated Cardboard 

-5.99 

-8.49 

-3.51 

NA 

-1.05 

Magazines/Third-class Mail 

-8.35 

-8.65 

-2.77 

NA 

-0.17 

Newspaper 

-4.01 

-5.09 

-1.92 

NA 

0.13 

Office Paper 

-9.94 

-10.23 

-4.79 

NA 

-2.57 

Phonebooks 

-5.45 

-5.45 

-1.79 

NA 

0.13 

Textbooks 

-11.11 

-11.41 

-5.05 

NA 

-2.57 

Dimensional Lumber 

-1.53 

NA 

-1.97 

NA 

-0.29 

Medium-density Fiberboard 

-1.73 

NA 

-1.98 

NA 

-0.29 

Food Discards 

NA 

NA 

NA 

-0.92 

-0.90 

Yard Trimmings 

Mixed Paper 

NA 

NA 

NA 

0.02 

0.00 

Broad Definition 

NA 

NA 

-3.89 

NA 

-1.00 

Residential Definition 

NA 

NA 

-3.79 

NA 

-0.90 

Office Paper Definition 

NA 

NA 

-3.88 

NA 

-1.06 

Mixed Metals 

NA 

NA 

-5.29 

NA 

-1.10 

Mixed Plastics 

NA 

NA 

-1.53 

NA 

0.95 

Mixed Recyclables 

NA 

NA 

-3.05 

NA 

-0.75 

Mixed Organics 

NA 

NA 

NA 

-0.43 

-0.43 

Mixed MSW as Disposed 

NA 

NA 

NA 

NA 

-0.55 

Carpet 

-4.03 

-4.03 

-7.22 

NA 

0.35 

Personal Computers 

-55.51 

-55.51 

-2.30 

NA 

-0.24 

Clay Bricks 

-0.32 

-0.32 

-0.04 

NA 

-0.04 

Concrete 

-0.04 

-0.04 

-0.05 

NA 

-0.04 

Fly Ash 

-0.04 

-0.04 

-0.91 

NA 

-0.04 

Tires 

-4.02 

-4.02 

-1.86 e 

NA 

0.14 


Note that totals may not add due to rounding, and more digits may be displayed than are significant. 

NA: Not applicable, or in the case of composting of paper, not analyzed. 

a Values for landfilling reflect projected national average methane recovery in year 2004. 

b Source reduction assumes initial production using the current mix of virgin and recycled inputs. 

Calculation is based on assuming zero net emissions for composting. 

d Values are for mass burn facilities with national average rate of ferrous recovery. 

e Recycling of tires, as modeled in this analysis, consists only of retreading the tires. 


128 









Exhibit B-3 

GHG Emissions for Source Reduction (MTC02E/Ton of Material Source Reduced) 
Emissions Measured from a Waste Generation Reference Point 3 


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Exhibit B-4 

Recycling (GHG Emissions in MTC02E/Ton) 
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Exhibit B-7 

Landfilling (GHG Emissions in MTC02E/Ton) 

Values for Landfill Methane and Net Emissions Reflect Projected National Average Methane Recovery in year 2003. 

Emissions Measured from a Waste Generation Reference Point 3 


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a Under the accounting convention used in this analysis, emissions are quantified from a waste generation reference point (once the material has already undergone the raw materials acquisition 
and manufacturing phase). 













This page intentionally left blank. 


134 


APPENDIX C: ROADMAP FROM THE SECOND EDITION 


Since the release of the second edition of the report, numerous adjustments and improvements 
have been made to the underlying data and methodology supporting the life-cycle emission factors. This 
new edition of the report has incorporated these updates, and the improvements are also reflected in the 
latest versions of the WAste Reduction Model (WARM), Recycled Content (ReCon) Tool and Durable 
Goods Calculator (DGC). 1 This appendix provides a brief explanation of the changes made to the 
underlying data and provides details on the latest emission factors being used in this edition of the report. 
Additional details on these changes can be found in the body of this report. 

The primary changes and improvements to the life-cycle analysis since the 2002 report include 
the following: 

• Developed emission factors for eight new material types: copper wire, clay bricks, concrete, fly 
ash, tires, carpet, personal computers, and mixed metals. As information on these additional 
material types became available, the list of material types has been expanded to provide greater 
capture of the municipal solid waste stream. 

• Updated the national average fuel mix for utility-generated electricity based on information from 
the DOE, EIA, Annual Energy Review: 2004 on electric utility consumption of fossil fuels. 

• Incorporated new energy data into calculations of utility offsets; 

• Updated the characterization of the municipal waste stream based on the 2003 Municipal Solid 
Waste in the United States: Facts and Figures report. This characterization study is used to 
develop emission factors for several of the “mixed” material types (e.g., mixed metals, mixed 
MSW). 

• Revised the “current mix” values for virgin and recycled content of materials based on data 
obtained from Franklin Associates Ltd. 

• Incorporated open loop recycling of corrugated cardboard and mixed paper into the life-cycle 
methodology. This provides a more accurate picture of the recycling of these materials such that 
recycled corrugated cardboard does not always go into the production of new corrugated 
cardboard. 

• Added retail transportation (factory to point-of-sale) to the methodology utilizing commodity 
transportation data from the U.S. Census Bureau. 

• Updated data on the behavior of organic materials in the landfill environment based on recent 
studies by Dr. Barlaz of NC State University. 

• Updated information on landfill gas recovery rates to reflect latest values from the U.S. Inventory 
of Greenhouse Gas Emissions and Sinks; 

• Updated the forest carbon sequestration factors based on revised estimates from the U.S. 
Department of Agriculture—Forest Service. 

It should be noted that the fundamental aspects of the methodology reported in the 2002 report 
remain unchanged and this appendix is designed to communicate changes in the GHG emission factors 
that have occurred since the publication of the 2002 report. 

The following pages present tables showing the net emission factors presented in the 2002 report, 
in order for readers to see how they have changed. Because numerous factors have been updated, 


! Available online at http://vosemite.eDa.gov/oar/globalwamiing.nsf/content/ActionsWaste.html . under the “tools” 
heading. 


135 






including the average fuel mix and forest carbon sequestration values, all emission factors for source 
reduction, recycling, combustion, and landfilling presented in the tables below have changes; however, in 
some cases the change may not be apparent, due to rounding. The emission factors for composting have 
not changed. 

Exhibit C-l presents the net emission factors for source reduction from the 2002 report, as well as 
the components used to generate the net emission factors. 

Exhibit C-2 presents the net emission factors for recycling from the 2002 report, as well as the 
components used to generate the net emission factors. In addition to the general changes outlined at the 
beginning of the Appendix, the benefits of recycling aluminum have been revised. The process energy 
values were updated to incorporate revised fuel mix data for the production of aluminum sheet and 
transportation energy values were also updated based on energy data obtained from a personal computer 
life-cycle analysis performed by Franklin Associates Ltd. The process non-energy values were revised to 
incorporate additional anode production data provided by Franklin Associates Ltd. along with the latest 
data on perfluorocarbon emission characteristics for aluminum smelting. 

Exhibit C-3 presents the net emission factors for composting yard trimmings from the 2002 
report, as well as the components used to generate the net emission factors. Although compost emission 
factors were developed for grass, leaves and branches, and new columns were added to the summary table 
to accommodate potential C02 and CH4 emissions from composting, these changes had no impact on the 
net emission factors. 

Exhibit C-4 presents the net emission factors for combustion from the 2002 report, as well as the 
components used to generate the net emission factors. 

Exhibit C-5 presents the net emission factors for landfilling from the 2002 report, as well as the 
components used to generate the net emission factors. The total carbon sequestration factors for coated 
paper, newsprint, leaves and grass and the landfill CH 4 yields for corrugated cardboard, office paper, food 
discards, and branches were updated based on methodology changes suggested by Dr. Mort Barlaz of 
NCSU. 


136 


GHG Emissions for Source Reduction 
(MTCE/Ton of Material Source Reduced) 


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based on a weighted average of closed- and open-loop recycling for mixed paper. All other estimates are for closed-loop recycling. 









Exhibit C-3 


Net GHG Emissions from Composting 


(In MTCE Per Short Ton of Yard Trimmings Composted) 


Emission/ Storage Factor (for 2010) 

Soil Carbon Restoration 

Increased 

Humus 

Formation 

Transportation 

Emissions 

Net Carbon Flux 

Unweighted 

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C that is not 
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estimate 




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Exhibit C-4 

Gross Emissions of GHGs from MSW Combustion (MTCE/Ton) 


(a) 

Material Combusted 

(b) 

Combustion C0 2 
Emissions From 

Non-Biomass 
Per Ton 
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(e = b + c + d) 
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Ton Combusted 

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Note that Exhibits 6-1,6-2, and 6-5 show coated paper but not mixed paper; 
mixed paper is shown in the summary exhibit (Exhibit 6-6). 

The summary values for mixed paper are based on the proportions of the four paper types (newspaper, 

office paper corrugated cardboard, and coated paper) that comprise the different "mixed paper" definitions. 
I ne values tor phone books and textbooks are proxies, based on newspaper and ottice paper, respectively. 


139 

















Exhibit C-5 

Net GHG Emissions from Landfilling 



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library 


September 2006 
EPA 530-R-06-004 



Recycled/Recyclable 

Printed with Vegetable Oil-Based Inks on 

Recycled Paper (Minimum 50 percent Postconsumer) 

Process Chlorine Free 











